U.S. patent application number 17/393250 was filed with the patent office on 2021-11-25 for extracting audiovisual features from digital components.
This patent application is currently assigned to Google LLC. The applicant listed for this patent is Google LLC. Invention is credited to Gaurav Bhaya, Xuemei GU, Gangjiang Li, Robert Stets, Boon-Lock Yeo.
Application Number | 20210365628 17/393250 |
Document ID | / |
Family ID | 1000005756736 |
Filed Date | 2021-11-25 |
United States Patent
Application |
20210365628 |
Kind Code |
A1 |
Yeo; Boon-Lock ; et
al. |
November 25, 2021 |
EXTRACTING AUDIOVISUAL FEATURES FROM DIGITAL COMPONENTS
Abstract
Systems and methods for extracting audiovisual features from
images and other digital components. A data processing system can
extract image data and image features from an input image. The data
processing system can match the image features to the image
features of a plurality of image to identify candidate images. A
second image can be selected from the candidate images based on a
request that the data processing system received with the input
image.
Inventors: |
Yeo; Boon-Lock; (Los Altos
Hills, CA) ; GU; Xuemei; (Mountain View, CA) ;
Li; Gangjiang; (Shanghai, CN) ; Bhaya; Gaurav;
(Sunnyvale, CA) ; Stets; Robert; (Mountain View,
CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Google LLC |
Mountain View |
CA |
US |
|
|
Assignee: |
Google LLC
Mountain View
CA
|
Family ID: |
1000005756736 |
Appl. No.: |
17/393250 |
Filed: |
August 3, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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15638304 |
Jun 29, 2017 |
11093692 |
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17393250 |
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15190897 |
Jun 23, 2016 |
10586127 |
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15638304 |
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13295507 |
Nov 14, 2011 |
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15190897 |
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15395689 |
Dec 30, 2016 |
10972530 |
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15638304 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 40/134 20200101;
G06K 9/6201 20130101; G06F 16/583 20190101; G06K 9/00087 20130101;
G06K 9/46 20130101; G06F 40/279 20200101; G06F 16/434 20190101 |
International
Class: |
G06F 40/134 20060101
G06F040/134; G06K 9/00 20060101 G06K009/00; G06F 16/432 20060101
G06F016/432; G06F 16/583 20060101 G06F016/583; G06F 40/279 20060101
G06F040/279 |
Claims
1.-20. (canceled)
21. A system, comprising: a data processing system comprising at
least one hardware processor coupled to memory to: receive, from a
computing device, a term and an image that is different from the
term; retrieve, from a data repository, content data for each of a
plurality of content items, the content data comprising image
features; extract an image feature from the image, the image
feature including at least one of an edge, a corner feature, or a
ridge feature; select a content item from the plurality of content
items based at least in part on the term and on matches between the
image features of the plurality of content items and the at least
one of the edge, the corner feature, or the ridge feature of the
image; and transmit the content item to the computing device.
22. The system of claim 21, comprising: the data processing system
to receive a request from the computing device, the request
comprising a query comprising the term.
23. The system of claim 21, comprising: the data processing system
to receive the term via an audio-based input signal detected by the
computing device.
24. The system of claim 21, comprising the data processing system
to: select candidate content items from the plurality of content
items based on matches between the image features of the plurality
of content items and the at least one of the edge, the corner
feature, or the ridge feature of the image; and select the content
item from the candidate content items.
25. The system of claim 24, comprising: the data processing system
to select the content item from the candidate content items based
at least in part on the term.
26. The system of claim 21, wherein the image is captured by a
camera associated with the computing device.
27. The system of claim 21, comprising the data processing system
to: apply an image feature detection to the image to extract the
image feature; and apply the image feature detection to each of the
plurality of content items.
28. The system of claim 21, comprising the data processing system
to: extract a plurality of image features from the image; extract a
second plurality of image features from each of the plurality of
content items; select candidate content items from the plurality of
content items by matching a first predetermined number of the
plurality of image features with a second predetermined number of
the second plurality of image features; and select the content item
from the candidate content items.
29. The system of claim 21, comprising the data processing system
to: receive data packets comprising a request; parse the request to
identify the term and a trigger keyword corresponding to the
request; and select the content item from the plurality of content
items based on the trigger keyword.
30. The system of claim 21, comprising the data processing system
to: generate an action data structure based on the term; and
transmit the action data structure to a service provider computing
device to cause the service provider computing device to invoke a
conversational application programming interface and establish a
communication session between the service provider computing device
and the computing device.
31. A method, comprising: receiving, by a data processing system
comprising at least one hardware processor coupled to memory, from
a computing device, a term and an image that is different from the
term; retrieving, by the data processing system from a data
repository, content data for each of a plurality of content items,
the content data comprising image features; extracting, by the data
processing system, an image feature from the image, the image
feature including at least one of an edge, a corner feature, or a
ridge feature; selecting, by the data processing system, a content
item from the plurality of content items based at least in part on
the term and on matches between the image features of the plurality
of content items and the at least one of the edge, the corner
feature, or the ridge feature of the image; and transmitting, by
the data processing system, the content item to the computing
device.
32. The method of claim 31, comprising: receiving, by the data
processing system, a request from the computing device, the request
comprising a query comprising the term.
33. The method of claim 31, comprising: receiving, by the data
processing system, the term via an audio-based input signal
detected by the computing device.
34. The method of claim 31, comprising: selecting, by the data
processing system, candidate content items from the plurality of
content items based on matches between the image features of the
plurality of content items and the at least one of the edge, the
corner feature, or the ridge feature of the image; and selecting,
by the data processing system, the content item from the candidate
content items.
35. The method of claim 34, comprising: selecting, by the data
processing system, the content item from the candidate content
items based at least in part on the term.
36. The method of claim 31, wherein the image is captured by a
camera associated with the computing device.
37. The method of claim 31, comprising: applying, by the data
processing system, an image feature detection to the image to
extract the image feature; and applying, by the data processing
system, the image feature detection to each of the plurality of
content items.
38. The method of claim 31, comprising: extracting, by the data
processing system, a plurality of image features from the image;
extracting, by the data processing system, a second plurality of
image features from each of the plurality of content items;
selecting, by the data processing system, candidate content items
from the plurality of content items by matching a first
predetermined number of the plurality of image features with a
second predetermined number of the second plurality of image
features; and selecting, by the data processing system, the content
item from the candidate content items.
39. The method of claim 31, comprising: receiving, by the data
processing system, data packets comprising a request; parsing, by
the data processing system, the request to identify the term and a
trigger keyword corresponding to the request; and selecting, by the
data processing system, the content item from the plurality of
content items based on the trigger keyword.
40. The method of claim 31, comprising: generating, by the data
processing system, an action data structure based on the term; and
transmitting, by the data processing system, the action data
structure to a service provider computing device to cause the
service provider computing device to invoke a conversational
application programming interface and establish a communication
session between the service provider computing device and the
computing device.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] The present application claims the benefit of priority under
35 U.S.C. .sctn. 120 as a continuation of U.S. patent application
Ser. No. 15/638,304, filed Jun. 29, 2017, which claims the benefit
of priority under 35 U.S.C. .sctn. 120 as a continuation-in-part of
U.S. patent application Ser. No. 15/190,897, filed Jun. 23, 2016,
which claims the benefit of priority under 35 U.S.C. .sctn. 120 as
a continuation of U.S. patent application Ser. No. 13/295,507,
filed Nov. 14, 2011. The application also claims the benefit of
priority under 35 U.S.C. .sctn. 120 as a continuation-in-part of
U.S. patent application Ser. No. 15/395,689, filed Dec. 30, 2016.
Each of the foregoing applications are hereby incorporated by
reference in their entirety.
BACKGROUND
[0002] Electronic online documents can include content elements.
These content elements can be defined for presentation with or
within a webpage. Text content of the webpage can be used to
identify relevant content. However, some text content may not be
relevant to the topic of the webpage. Furthermore, some webpages
may lack text content.
BRIEF SUMMARY
[0003] At least one aspect is direct to a system to extract image
features from input requests. The system can include a recognition
engine that can be executed by a data processing system. The
recognition engine can receive, from a computing device, a first
request that can include a first image. The recognition engine can
retrieve, from a data repository, image data for each of a
plurality of images. The image data can include image features. The
recognition engine can extract an image feature from the first
image. The recognition engine can select candidate images from the
plurality of images by determining matches between the image
features of the plurality of images and the image feature from the
first image. The recognition engine can select a second image from
the candidate images based on the request. The system can also
include a network interface of the data processing system to
transmit the second image to the computing device.
[0004] At least one aspect is direct to a method to extract image
features from input requests. The method can include receiving,
from a computing device by a data processing system, a first
request that can include a first image. The method can include
retrieving, from a data repository by the data processing system,
image data for each of a plurality of images. The image data can
include image features. The method can include extracting, by a
recognition engine executed by the data processing system, an image
feature from the first image. The method can include selecting, by
the data processing system, candidate images from the plurality of
images by determining matches between the image features of the
plurality of images and the image feature from the first image. The
method can include selecting, by the data processing system, a
second image from the candidate images based on the request. The
method can include transmitting, via a network interface, the
second image to the computing device.
[0005] At least one aspect is directed to a system for extracting
audiovisual features from online document elements. A recognition
engine executed on a data processing system having one or more
processors can identify a first audiovisual content element on an
online document, the first audiovisual content element including
image data. The recognition can retrieve a second audiovisual
content element from a content provider database, the second
audiovisual content element including image data. The recognition
engine can extract an image feature from the first audiovisual
content element by applying an image feature detection to the image
data of the first audiovisual content element. The recognition
engine can extract an image feature from the second audiovisual
content element by applying the image feature detection to the
image data of the second audiovisual content element. The
recognition engine can determine an image feature match between the
image feature of the first audiovisual content element and the
image feature of the second audiovisual content element. The
recognition engine can select the second audiovisual content
element for display by the client device on the online document
based on the image feature match. The data processing system can
transmit, via a network interface, the second audiovisual content
element to the client device for insertion by the client device in
a content slot of the online document, responsive to the selection
of the second audiovisual content element.
[0006] At least one aspect is directed to a method of extracting
audiovisual features from online document elements. A recognition
engine executing on a data processing system having one or more
processors can identify a first audiovisual content element on an
online document, the first audiovisual content element including
image data. The recognition can retrieve a second audiovisual
content element from a content provider database, the second
audiovisual content element including image data. The recognition
engine can extract an image feature from the first audiovisual
content element by applying an image feature detection to the image
data of the first audiovisual content element. The recognition
engine can extract an image feature from the second audiovisual
content element by applying the image feature detection to the
image data of the second audiovisual content element. The
recognition engine can determine an image feature match between the
image feature of the first audiovisual content element and the
image feature of the second audiovisual content element. The
recognition engine can select the second audiovisual content
element for display by the client device on the online document
based on the image feature match. The data processing system can
transmit, via a network interface, the second audiovisual content
element to the client device for insertion by the client device in
a content slot of the online document, responsive to the selection
of the second audiovisual content element.
[0007] These and other aspects and implementations are discussed in
detail below. The foregoing information and the following detailed
description include illustrative examples of various aspects and
implementations, and provide an overview or framework for
understanding the nature and character of the claimed aspects and
implementations. The drawings provide illustration and a further
understanding of the various aspects and implementations, and are
incorporated in and constitute a part of this specification.
BRIEF DESCRIPTION OF THE DRAWINGS/FIGURES
[0008] The accompanying drawings are not intended to be drawn to
scale. Like reference numbers and designations in the various
drawings indicate like elements. For purposes of clarity, not every
component may be labeled in every drawing. In the drawings:
[0009] FIGS. 1A and 1B illustrate digital component selection
examples.
[0010] FIG. 1C is an illustration of a system to route packetized
actions via a computer network.
[0011] FIG. 2 is a block diagram of an example environment in which
a digital component system manages digital component distribution
services.
[0012] FIG. 3 is a flow diagram illustrating a method for providing
digital components based on content of a resource.
[0013] FIG. 4 is a flow diagram illustrating a further method for
providing digital components based on content of a resource.
[0014] FIG. 5 is a swim lane diagram illustrating a process for
providing digital components based on content of a resource,
according to an embodiment.
[0015] FIG. 6 is a system diagram that can be used to implement
embodiments described herein.
[0016] FIG. 7 is an illustration of an operation of a system to
route packetized actions via a computer network.
[0017] FIG. 8 is an illustration of an operation of a system to
route packetized actions via a computer network.
[0018] FIG. 9 illustrates a block diagram of an example method to
extract image features from input requests.
DETAILED DESCRIPTION
[0019] Following below are more detailed descriptions of various
concepts related to, and implementations of, methods, apparatuses,
and systems of routing packetized actions via a computer network.
The various concepts introduced above and discussed in greater
detail below may be implemented in any of numerous ways.
[0020] The present disclosure is generally directed to improving
the efficiency and effectiveness of information transmission and
processing over disparate computing resources. It is challenging
for disparate computing resource to efficiently process, and
consistently and accurately parse audio-based instructions in a
voice-based computing environment. For example, the disparate
computing resources may not have access to the same voice models,
or may have access to out of date or unsynchronized voice models
that can make it challenging to accurately and consistently parse
the audio-based instructions.
[0021] Systems and methods of the present disclosure are generally
directed to a data processing system that routes packetized actions
via a computer network. The data processing system can process the
voice-based input using specifically voice models that are trained
based on aggregate voice to parse the voice-based instructions and
create an action data structure. The data processing system can
transmit the action data structure to one or more component of the
data processing system or third-party provider devices, which can
also be referred to as service provider computing device, thereby
allowing the third-party provider device to process the action data
structure without having to process the voice-based input. By
processing the voice-based input for a plurality of third-party
provider devices, the data processing system can improve the
reliability, efficiency, and accuracy with which voice-based
instructions are processed and performed.
[0022] The present solution can reduce resource consumption,
processor utilization, battery consumption, bandwidth utilization,
size of an audio file, or amount of time consumed by a speaker by
parsing voice-based instructions from an end user, constructing an
action data structure using a template, and routing the action data
structure to a corresponding third-party provider.
[0023] A digital component or a content item may refer to any form
of communication in which one or more products, services, ideas,
messages, people, organizations, or other items are identified and
promoted or otherwise communicated. The digital components are not
limited to commercial promotions or other communications. a digital
component may be a public service announcement or any other type of
notice, such as a broadcast or a public notice published in printed
or electronic press. In some implementations, a digital component
may be referred to or included in sponsored content. A digital
component can include one or more content items. A digital
component can be a content item. The digital component can be any
type of digital file or document, such as a webpage, image file,
video file, audio file, or action data structure.
[0024] Digital components (or promotional or digital content items
generally) may be communicated via various mediums and in a number
of forms. In some examples, digital components may be communicated
through an interactive medium, such as the Internet, and may
include graphical digital components (e.g., banner digital
components), textual digital components, image digital components,
audio digital components, video digital components, digital
components combining one of more of the foregoing formats, or any
form of electronically delivered digital component. Digital
Components may include embedded information, such as embedded
media, links, meta-information, and/or machine executable
instructions. Digital Components also may be communicated through
RSS (Really Simple Syndication) feeds, radio channels, television
channels, print media, and other media.
[0025] The term "digital component" can refer to both a single
"creative" and a "digital component group." A creative can refer to
any entity that represents one digital component impression. a
digital component impression can refer to any form of presentation
of a digital component, such that the digital component is viewable
or receivable by a user. In some examples, a digital component
impression may occur when a digital component is displayed on a
display device of a user access device. a digital component group
can refer, for example, to an entity that represents a group of
creatives that share a common characteristic, such as having the
same digital component targeting criteria. Digital Component groups
can be used to create a digital component campaign. For
convenience, digital components, creatives, content items, and
other digital content can be collectively referred to as "digital
components" herein.
[0026] Digital Components may be included on resources provided by
content provider computing devices, which can also be referred to
as publisher computing devices. For example, a content provider
computing device may specify one or more areas on a resource, such
as a webpage, where digital components are to be displayed. A
content provider computing device may also provide a resource such
as an application to user devices, and may allow digital components
to be displayed in the application. Relevant digital components may
be identified based on text content included on the resource. Some
resources include more multimedia content, such as image content,
audio content, or video content, than text content. The text
content may not be related to the multimedia content. Thus,
irrelevant digital components may be provided. Further, certain
resources include no text content. Embodiments identify relevant
digital components based on multimedia content included on a
resource provided by a content provider computing device.
[0027] FIGS. 1A-1C illustrate example 100 of providing digital
components in response to multimedia content on a resource. In FIG.
1A, a user may request a content provider computing device
resource, such as webpage 110. Webpage 110 includes one or more
multimedia elements, such as image 111 and video 113. Webpage 110
may also include text content. Webpage 110 may also include one or
more digital component slots 112A and 112B. When a user requests
the content provider computing device webpage, a request for
digital components may be sent to a data processing system 102,
which accesses one or more digital components 106. Each digital
component 106 may be associated with one or more digital component
multimedia elements, which may include images, video data, or audio
data. For example, digital component 106A is associated with
digital component image 107. Digital Component 106B is can be
associated with video content.
[0028] The data processing system 102 includes a recognition engine
104 Recognition engine 104 may recognize one or more features of
image 111. In one embodiment, the images are sent with the request
for digital components to the data processing system 102. In
another embodiment, features associated with the images are sent to
the data processing system 102. Further, recognition engine 104 may
identify features that match between recognized features in image
111 and features of images associated with one or more digital
components 106. For example, recognized features of image 111A may
match features of digital component image 107. Image features may
include, for example and without limitation, edges, corner
features, interest points, blobs or regions of interest, or ridge
features. Based on matching features between image 111 and the
images associated with digital components 106, a relevant digital
component may be identified and provided to the content provider
computing device to be displayed on webpage 110 in one of the
digital component slots 112A or 112B.
[0029] In FIG. 1B, a second user may request a second content
provider computing device resource, such as webpage 160. webpage
160 includes one or more multimedia elements, such as video 161 and
image 163, and may include text content. webpage 160 also includes
one or more digital component slots 162A and 162B. When a user
requests the webpage 160, a request for digital components may be
sent to a data processing system 102, which accesses one or more
digital components 106. Each digital component 106 may be
associated with one or more digital component keywords. For
example, digital component 106C is associated with digital
component keyword 109C. Further, each digital component 106 may be
associated with one or more text labels for a digital component
multimedia element associated with a digital component. For
example, digital component 106D may be associated with image 107D,
which is associated with a text label.
[0030] In one embodiment, the multimedia elements are sent with the
request for digital components to the data processing system 102.
In another embodiment, text labels associated with the multimedia
elements are sent to the data processing system 102. Recognition
engine 104 may identify a text label associated with video 161.
Text labels associated with images and multimedia elements may be,
for example and without limitation, query terms input by a user,
which resulted in the images or other multimedia elements being
displayed to a user and selected by the user. Text labels may also
include metadata associated with a multimedia element. Further,
text labels or keywords associated with digital components 106, or
text labels associated with multimedia elements associated with
digital components 106 may be identified. For example, recognition
engine 104 may identify keyword 109C as being responsive to a text
label associated with video 161. For example, text label "daisy"
can match keyword "daisy", or be identified as responsive to
keyword "flower". Based on the identification of responsiveness,
digital component 106C may be identified as a relevant digital
component and provided to the content provider computing device to
be displayed on webpage 160 in one of the digital component slots
162A or 162B.
[0031] FIG. 1C illustrates an example system 100 to route
packetized actions via a computer network. The system 100 can
include content selection infrastructure. The system 100 can
include a data processing system 102. The data processing system
102 can communicate with one or more of a content provider
computing device 106, service provider computing device 210, or
client computing device 206 via a network 105. The network 105 can
include computer networks such as the Internet, local, wide, metro,
or other area networks, intranets, satellite networks, and other
communication networks such as voice or data mobile telephone
networks. The network 105 can be used to access information
resources such as web pages, web sites, domain names, or uniform
resource locators that can be presented, output, rendered, or
displayed on at least one computing device 206, such as a laptop,
desktop, tablet, personal digital assistant, smart phone, portable
computers, or speaker. For example, via the network 105 a user of
the computing device 206 can access information or data provided by
a service provider 210 or content provider 106. The computing
device 206 may or may not include a display; for example, the
computing device may include limited types of user interfaces, such
as a microphone and speaker. In some cases, the primary user
interface of the computing device 206 may be a microphone and
speaker.
[0032] The network 105 can include or constitute a display network,
e.g., a subset of information resources available on the internet
that are associated with a content placement or search engine
results system, or that are eligible to include third-party content
items as part of a content item placement campaign. The network 105
can be used by the data processing system 102 to access information
resources such as web pages, web sites, domain names, or uniform
resource locators that can be presented, output, rendered, or
displayed by the client computing device 206. For example, via the
network 105 a user of the client computing device 206 can access
information or data provided by the content provider computing
device 106 or the service provider computing device 210.
[0033] The network 105 may be any type or form of network and may
include any of the following: a point-to-point network, a broadcast
network, a wide area network, a local area network, a
telecommunications network, a data communication network, a
computer network, an ATM (Asynchronous Transfer Mode) network, a
SONET (Synchronous Optical Network) network, a SDH (Synchronous
Digital Hierarchy) network, a wireless network and a wireline
network. The network 105 may include a wireless link, such as an
infrared channel or satellite band. The topology of the network 105
may include a bus, star, or ring network topology. The network may
include mobile telephone networks using any protocol or protocols
used to communicate among mobile devices, including advanced mobile
phone protocol ("AMPS"), time division multiple access ("TDMA"),
code-division multiple access ("CDMA"), global system for mobile
communication ("GSM"), general packet radio services ("GPRS") or
universal mobile telecommunications system ("UMTS"). Different
types of data may be transmitted via different protocols, or the
same types of data may be transmitted via different protocols.
[0034] The system 100 can include data processing system 102. The
data processing system 102 can include at least one logic device
such as a computing device having a processor to communicate via
the network 105, for example with the computing device 206, the
content provider device 106 (content provider 106), or the service
provider device 210 (or service provider 210). The data processing
system 102 can include at least one computation resource, server,
processor or memory. For example, the data processing system 102
can include a plurality of computation resources or servers located
in at least one data center. The data processing system 102 can
include multiple, logically-grouped servers and facilitate
distributed computing techniques. The logical group of servers may
be referred to as a data center, server farm or a machine farm. The
servers can also be geographically dispersed. A data center or
machine farm may be administered as a single entity, or the machine
farm can include a plurality of machine farms. The servers within
each machine farm can be heterogeneous--one or more of the servers
or machines can operate according to one or more type of operating
system platform.
[0035] Servers in the machine farm can be stored in high-density
rack systems, along with associated storage systems, and located in
an enterprise data center. For example, consolidating the servers
in this way may improve system manageability, data security, the
physical security of the system, and system performance by locating
servers and high-performance storage systems on localized
high-performance networks. Centralization of all or some of the
data processing system 102 components, including servers and
storage systems, and coupling them with advanced system management
tools allows more efficient use of server resources, which saves
power and processing requirements and reduces bandwidth usage.
[0036] The system 100 can include, access, or otherwise interact
with at least one service provider device 210. The service provider
device 210 can include at least one logic device such as a
computing device having a processor to communicate via the network
105, for example with the computing device 206, the data processing
system 102, or the content provider 106. The service provider
device 210 can include at least one computation resource, server,
processor or memory. For example, service provider device 210 can
include a plurality of computation resources or servers located in
at least one data center. The service provider device 210 can
include one or more component or functionality of the data
processing system 102.
[0037] The content provider computing device 106 can provide audio
based content items for display by the client computing device 206
as an audio output content item. The content item can include an
offer for a good or service, such as a voice based message that
states: "Would you like me to order you a taxi?" For example, the
content provider computing device 222 can include memory to store a
series of audio content items that can be provided in response to a
voice based query. The content provider computing device 106 can
also provide audio based content items (or other content items) to
the data processing system 102 where they can be stored in the data
repository 124. The data processing system 102 can select the audio
content items and provide (or instruct the content provider
computing device 222 to provide) the audio content items to the
client computing device 206. The audio based content items can be
exclusively audio or can be combined with text, image, or video
data.
[0038] The service provider device 210 can include, interface, or
otherwise communicate with at least one service provider natural
language processor component 142 and a service provider interface
144. The service provider computing device 210 can include at least
one service provider natural language processor (NLP) component 142
and at least one service provider interface 144. The service
provider NLP component 142 (or other components such as a direct
action API of the service provider computing device 210) can engage
with the client computing device 206 (via the data processing
system 102 or bypassing the data processing system 102) to create a
back-and-forth real-time voice or audio based conversation (e.g., a
session) between the client computing device 206 and the service
provider computing device 210. The service provider NLP 142 can
include one or more function or feature as the NLP component 171 of
the data processing system 102. For example, the service provider
interface 144 can receive or provide data messages to the direct
action API 116 of the data processing system 102. The service
provider computing device 210 and the content provider computing
device 106 can be associated with the same entity. For example, the
content provider computing device 106 can create, store, or make
available content items for a car sharing service, and the service
provider computing device 210 can establish a session with the
client computing device 206 to arrange for a delivery of a taxi or
car of the car share service to pick up the end user of the client
computing device 206. The data processing system 102, via the
direct action API 116, the NLP component 171 or other components
can also establish the session with the client computing device,
including or bypassing the service provider computing device 210,
to arrange for example for a delivery of a taxi or car of the car
share service.
[0039] The computing device 206 can include, interface, or
otherwise communicate with at least one sensor 134, transducer 136,
audio driver 138, or pre-processor 140. The sensor 134 can include,
for example, an ambient light sensor, proximity sensor, temperature
sensor, accelerometer, gyroscope, motion detector, GPS sensor,
location sensor, microphone, or touch sensor. The transducer 136
can include a speaker or a microphone. The audio driver 138 can
provide a software interface to the hardware transducer 136. The
audio driver can execute the audio file or other instructions
provided by the data processing system 102 to control the
transducer 136 to generate a corresponding acoustic wave or sound
wave. The pre-processor 140 can be configured to detect a keyword
and perform an action based on the keyword. The pre-processor 140
can filter out one or more terms or modify the terms prior to
transmitting the terms to the data processing system 102 for
further processing. The pre-processor 140 can convert the analog
audio signals detected by the microphone into a digital audio
signal, and transmit one or more data packets carrying the digital
audio signal to the data processing system 102 via the network 105.
In some cases, the pre-processor 140 can transmit data packets
carrying some or all of the input audio signal responsive to
detecting an instruction to perform such transmission. The
instruction can include, for example, a trigger keyword or other
keyword or approval to transmit data packets that can include the
input audio signal to the data processing system 102.
[0040] The client computing device 206 can be associated with an
end user that enters voice queries as audio input into the client
computing device 206 (via the sensor 134) and receives audio output
in the form of a computer generated voice that can be provided from
the data processing system 102 (or the content provider computing
device 106 or the service provider computing device 210) to the
client computing device 206, output from the transducer 136 (e.g.,
a speaker). The computer generated voice can include recordings
from a real person or computer generated language.
[0041] The data repository 124 can include one or more local or
distributed databases, and can include a database management
system. The data repository 124 can include computer data storage
or memory and can store one or more parameters 126, one or more
policies 128, content data 130, or templates 132 among other data.
The parameters 126, policies 128, and templates 132 can include
information such as rules about a voice based session between the
client computing device 206 and the data processing system 102 (or
the service provider computing device 210). The content data 130
can include content items for audio output or associated metadata,
as well as input audio messages that can be part of one or more
communication sessions with the client computing device 206.
[0042] The data processing system 102 can include a content
placement system having at least one computation resource or
server. The data processing system 102 can include, interface, or
otherwise communicate with at least one interface 170. The data
processing system 102 can include, interface, or otherwise
communicate with at least one natural language processor component
171. The data processing system 102 can include, interface, or
otherwise communicate with at least one direct action application
programming interface ("API") 116. The data processing system 102
can include, interface, or otherwise communicate with at least one
session handler 114. The data processing system 102 can include,
interface, or otherwise communicate with at least one content
selector component 118. The data processing system 102 can include,
interface, or otherwise communicate with at least one audio signal
generator 122. The data processing system 102 can include,
interface, or otherwise communicate with at least one data
repository 124. The at least one data repository 124 can include or
store, in one or more data structures or databases, parameters 126,
policies 128, content data 130, or templates 132. Parameters 126
can include, for example, thresholds, distances, time intervals,
durations, scores, or weights. Content data 130 can include, for
example, content campaign information, content groups, content
selection criteria, content item objects or other information
provided by a content provider 106 or obtained or determined by the
data processing system to facilitate content selection. The content
data 130 can include, for example, historical performance of a
content campaign.
[0043] The interface 170, natural language processor component 171,
session handler 114, direct action API 116, content selector
component 118, or audio signal generator component 122 can each
include at least one processing unit or other logic device such as
programmable logic array engine, or module configured to
communicate with the database repository or database 124. The
interface 170, natural language processor component 171, session
handler 114, direct action API 116, content selector component 118,
audio signal generator component 122 and data repository 124 can be
separate components, a single component, or part of the data
processing system 102. The system 100 and its components, such as a
data processing system 102, can include hardware elements, such as
one or more processors, logic devices, or circuits.
[0044] The data processing system 102 can obtain anonymous computer
network activity information associated with a plurality of
computing devices 206. A user of a computing device 206 can
affirmatively authorize the data processing system 102 to obtain
network activity information corresponding to the user's computing
device 206. For example, the data processing system 102 can prompt
the user of the computing device 206 for consent to obtain one or
more types of network activity information. The identity of the
user of the computing device 206 can remain anonymous and the
computing device 206 can be associated with a unique identifier
(e.g., a unique identifier for the user or the computing device
provided by the data processing system or a user of the computing
device). The data processing system can associate each observation
with a corresponding unique identifier.
[0045] A content provider 106 can establish an electronic content
campaign. The electronic content campaign can be stored as content
data 130 in data repository 124. An electronic content campaign can
refer to one or more content groups that correspond to a common
theme. A content campaign can include a hierarchical data structure
that includes content groups, content item data objects, and
content selection criteria. To create a content campaign, content
provider 106 can specify values for campaign level parameters of
the content campaign. The campaign level parameters can include,
for example, a campaign name, a preferred content network for
placing content item objects, a value of resources to be used for
the content campaign, start and end dates for the content campaign,
a duration for the content campaign, a schedule for content item
object placements, language, geographical locations, type of
computing devices on which to provide content item objects. In some
cases, an impression can refer to when a content item object is
fetched from its source (e.g., data processing system 102 or
content provider 106), and is countable. In some cases, due to the
possibility of click fraud, robotic activity can be filtered and
excluded, as an impression. Thus, in some cases, an impression can
refer to a measurement of responses from a Web server to a page
request from a browser, which is filtered from robotic activity and
error codes, and is recorded at a point as close as possible to
opportunity to render the content item object for display on the
computing device 206. In some cases, an impression can refer to a
viewable or audible impression; e.g., the content item object is at
least partially (e.g., 20%, 30%, 30%, 40%, 50%, 60%, 70%, or more)
viewable on a display device of the client computing device 206, or
audible via a speaker 136 of the computing device 206. A click or
selection can refer to a user interaction with the content item
object, such as a voice response to an audible impression, a
mouse-click, touch interaction, gesture, shake, audio interaction,
or keyboard click. A conversion can refer to a user taking a
desired action with respect to the content item objection; e.g.,
purchasing a product or service, completing a survey, visiting a
physical store corresponding to the content item, or completing an
electronic transaction.
[0046] The content provider 106 can further establish one or more
content groups for a content campaign. A content group includes one
or more content item objects and corresponding content selection
criteria, such as keywords, words, terms, phrases, geographic
locations, type of computing device, time of day, interest, topic,
or vertical. Content groups under the same content campaign can
share the same campaign level parameters, but may have tailored
specifications for particular content group level parameters, such
as keywords, negative keywords (e.g., that block placement of the
content item in the presence of the negative keyword on main
content), bids for keywords, or parameters associated with the bid
or content campaign.
[0047] To create a new content group, the content provider can
provide values for the content group level parameters of the
content group. The content group level parameters include, for
example, a content group name or content group theme, and bids for
different content placement opportunities (e.g., automatic
placement or managed placement) or outcomes (e.g., clicks,
impressions, or conversions). A content group name or content group
theme can be one or more terms that the content provider 106 can
use to capture a topic or subject matter for which content item
objects of the content group is to be selected for display. For
example, a car dealership can create a different content group for
each brand of vehicle it carries, and may further create a
different content group for each model of vehicle it carries.
Examples of the content group themes that the car dealership can
use include, for example, "Make A sports car" "Make B sports car,"
"Make C sedan," "Make C truck," "Make C hybrid," or "Make D
hybrid." An example content campaign theme can be "hybrid" and
include content groups for both "Make C hybrid" and "Make D
hybrid", for example.
[0048] The content provider 106 can provide one or more keywords
and content item objects to each content group. Keywords can
include terms that are relevant to the product or services of
associated with or identified by the content item objects. A
keyword can include one or more terms or phrases. For example, the
car dealership can include "sports car," "V-6 engine," "four-wheel
drive," "fuel efficiency," as keywords for a content group or
content campaign. In some cases, negative keywords can be specified
by the content provider to avoid, prevent, block, or disable
content placement on certain terms or keywords. The content
provider can specify a type of matching, such as exact match,
phrase match, or broad match, used to select content item
objects.
[0049] The content provider 106 can provide one or more keywords to
be used by the data processing system 102 to select a content item
object provided by the content provider 106. The content provider
106 can identify one or more keywords to bid on, and further
provide bid amounts for various keywords. The content provider 106
can provide additional content selection criteria to be used by the
data processing system 102 to select content item objects. Multiple
content providers 106 can bid on the same or different keywords,
and the data processing system 102 can run a content selection
process or ad auction responsive to receiving an indication of a
keyword of an electronic message.
[0050] The content provider 106 can provide one or more content
item objects for selection by the data processing system 102. The
data processing system 102 (e.g., via content selector component
118) can select the content item objects when a content placement
opportunity becomes available that matches the resource allocation,
content schedule, maximum bids, keywords, and other selection
criteria specified for the content group. Different types of
content item objects can be included in a content group, such as a
voice content item, audio content item, a text content item, an
image content item, video content item, multimedia content item, or
content item link. Upon selecting a content item, the data
processing system 102 can transmit the content item object for
rendering on a computing device 206 or display device of the
computing device 206. Rendering can include displaying the content
item on a display device, or playing the content item via a speaker
of the computing device 206. The data processing system 102 can
provide instructions to a computing device 206 to render the
content item object. The data processing system 102 can instruct
the computing device 206, or an audio driver 138 of the computing
device 206, to generate audio signals or acoustic waves.
[0051] The data processing system 102 can include an interface
component 170 designed, configured, constructed, or operational to
receive and transmit information using, for example, data packets.
The interface 170 can receive and transmit information using one or
more protocols, such as a network protocol. The interface 170 can
include a hardware interface, software interface, wired interface,
or wireless interface. The interface 170 can facilitate translating
or formatting data from one format to another format. For example,
the interface 170 can include an application programming interface
that includes definitions for communicating between various
components, such as software components.
[0052] The data processing system 102 can include an application,
script or program installed at the client computing device 206,
such as an app to communicate input audio signals to the interface
170 of the data processing system 102 and to drive components of
the client computing device to render output audio signals. The
data processing system 102 can receive data packets or other signal
that includes or identifies an audio input signal. For example, the
data processing system 102 can execute or run the NLP component 171
to receive or obtain the audio signal and parse the audio signal.
For example, the NLP component 171 can provide for interactions
between a human and a computer. The NLP component 171 can be
configured with techniques for understanding natural language and
allowing the data processing system 102 to derive meaning from
human or natural language input. The NLP component 171 can include
or be configured with technique based on machine learning, such as
statistical machine learning. The NLP component 171 can utilize
decision trees, statistical models, or probabilistic models to
parse the input audio signal. The NLP component 171 can perform,
for example, functions such as named entity recognition (e.g.,
given a stream of text, determine which items in the text map to
proper names, such as people or places, and what the type of each
such name is, such as person, location, or organization), natural
language generation (e.g., convert information from computer
databases or semantic intents into understandable human language),
natural language understanding (e.g., convert text into more formal
representations such as first-order logic structures that a
computer module can manipulate), machine translation (e.g.,
automatically translate text from one human language to another),
morphological segmentation (e.g., separating words into individual
morphemes and identify the class of the morphemes, which can be
challenging based on the complexity of the morphology or structure
of the words of the language being considered), question answering
(e.g., determining an answer to a human-language question, which
can be specific or open-ended), semantic processing (e.g.,
processing that can occur after identifying a word and encoding its
meaning in order to relate the identified word to other words with
similar meanings).
[0053] The NLP component 171 converts the audio input signal into
recognized text by comparing the input signal against a stored,
representative set of audio waveforms (e.g., in the data repository
124) and choosing the closest matches. The set of audio waveforms
can be stored in data repository 124 or other database accessible
to the data processing system 102. The representative waveforms are
generated across a large set of users, and then may be augmented
with speech samples from the user. After the audio signal is
converted into recognized text, the NLP component 171 matches the
text to words that are associated, for example via training across
users or through manual specification, with actions that the data
processing system 102 can serve.
[0054] The audio input signal can be detected by the sensor 134 or
transducer 136 (e.g., a microphone) of the client computing device
206. Via the transducer 136, the audio driver 138, or other
components the client computing device 206 can provide the audio
input signal to the data processing system 102 (e.g., via the
network 105) where it can be received (e.g., by the interface 170)
and provided to the NLP component 171 or stored in the data
repository 124.
[0055] The NLP component 171 can obtain the input audio signal.
From the input audio signal, the NLP component 171 can identify at
least one request or at least one trigger keyword corresponding to
the request. The request can indicate intent or subject matter of
the input audio signal. The trigger keyword can indicate a type of
action likely to be taken. For example, the NLP component 171 can
parse the input audio signal to identify at least one request to
leave home for the evening to attend dinner and a movie. The
trigger keyword can include at least one word, phrase, root or
partial word, or derivative indicating an action to be taken. For
example, the trigger keyword "go" or "to go to" from the input
audio signal can indicate a need for transport. In this example,
the input audio signal (or the identified request) does not
directly express an intent for transport, however the trigger
keyword indicates that transport is an ancillary action to at least
one other action that is indicated by the request.
[0056] The NLP component 171 can parse the input audio signal to
identify, determine, retrieve, or otherwise obtain the request and
the trigger keyword. For instance, the NLP component 171 can apply
a semantic processing technique to the input audio signal to
identify the trigger keyword or the request. The NLP component 171
can apply the semantic processing technique to the input audio
signal to identify a trigger phrase that includes one or more
trigger keywords, such as a first trigger keyword and a second
trigger keyword. For example, the input audio signal can include
the sentence "I need someone to do my laundry and my dry cleaning."
The NLP component 171 can apply a semantic processing technique, or
other natural language processing technique, to the data packets
comprising the sentence to identify trigger phrases "do my laundry"
and "do my dry cleaning". The NLP component 171 can further
identify multiple trigger keywords, such as laundry, and dry
cleaning. For example, the NLP component 171 can determine that the
trigger phrase includes the trigger keyword and a second trigger
keyword.
[0057] The NLP component 171 can filter the input audio signal to
identify the trigger keyword. For example, the data packets
carrying the input audio signal can include "It would be great if I
could get someone that could help me go to the airport", in which
case the NLP component 171 can filter out one or more terms as
follows: "it", "would", "be", "great", "if", "I", "could", "get",
"someone", "that", "could", or "help". By filtering out these
terms, the NLP component 171 may more accurately and reliably
identify the trigger keywords, such as "go to the airport" and
determine that this is a request for a taxi or a ride sharing
service.
[0058] In some cases, the NLP component can determine that the data
packets carrying the input audio signal includes one or more
requests. For example, the input audio signal can include the
sentence "I need someone to do my laundry and my dry cleaning." The
NLP component 171 can determine this is a request for a laundry
service and a dry cleaning service. The NLP component 171 can
determine this is a single request for a service provider that can
provide both laundry services and dry cleaning services. The NLP
component 171 can determine that this is two requests; a first
request for a service provider that performs laundry services, and
a second request for a service provider that provides dry cleaning
services. In some cases, the NLP component 171 can combine the
multiple determined requests into a single request, and transmit
the single request to a service provider device 210. In some cases,
the NLP component 171 can transmit the individual requests to
respective service provider devices 210, or separately transmit
both requests to the same service provider device 210.
[0059] The data processing system 102 can include a direct action
API 116 designed and constructed to generate, based on the trigger
keyword, an action data structure responsive to the request.
Processors of the data processing system 102 can invoke the direct
action API 116 to execute scripts that generate a data structure to
a service provider device 210 to request or order a service or
product, such as a car from a car share service. The direct action
API 116 can obtain data from the data repository 124, as well as
data received with end user consent from the client computing
device 206 to determine location, time, user accounts, logistical
or other information to allow the service provider device 210 to
perform an operation, such as reserve a car from the car share
service. Using the direct action API 116, the data processing
system 102 can also communicate with the service provider device
210 to complete the conversion by in this example making the car
share pick up reservation.
[0060] The direct action API 116 can execute a specified action to
satisfy the end user's intention, as determined by the data
processing system 102. Depending on the action specified in its
inputs, the direct action API 116 can execute code or a dialog
script that identifies the parameters required to fulfill a user
request. Such code can look-up additional information, e.g., in the
data repository 124, such as the name of a home automation service,
or it can provide audio output for rendering at the client
computing device 206 to ask the end user questions such as the
intended destination of a requested taxi. The direct action API 116
can determine necessary parameters and can package the information
into an action data structure, which can then be sent to another
component such as the content selector component 118 or to the
service provider computing device 210 to be fulfilled.
[0061] The direct action API 116 can receive an instruction or
command from the NLP component 171, or other component of the data
processing system 102, to generate or construct the action data
structure. The direct action API 116 can determine a type of action
in order to select a template from the template repository 132
stored in the data repository 124. Types of actions can include,
for example, services, products, reservations, or tickets. Types of
actions can further include types of services or products. For
example, types of services can include car share service, food
delivery service, laundry service, maid service, repair services,
or household services. Types of products can include, for example,
clothes, shoes, toys, electronics, computers, books, or jewelry.
Types of reservations can include, for example, dinner reservations
or hair salon appointments. Types of tickets can include, for
example, movie tickets, sports venue tickets, or flight tickets. In
some cases, the types of services, products, reservations or
tickets can be categorized based on price, location, type of
shipping, availability, or other attributes.
[0062] The direct action API 116, upon identifying the type of
request, can access the corresponding template from the template
repository 132. Templates can include fields in a structured data
set that can be populated by the direct action API 116 to further
the operation that is requested of the service provider device 210
(such as the operation of sending a taxi to pick up an end user at
a pickup location and transport the end user to a destination
location). The direct action API 116 can perform a lookup in the
template repository 132 to select the template that matches one or
more characteristic of the trigger keyword and request. For
example, if the request corresponds to a request for a car or ride
to a destination, the data processing system 102 can select a car
sharing service template. The car sharing service template can
include one or more of the following fields: device identifier,
pick up location, destination location, number of passengers, or
type of service. The direct action API 116 can populate the fields
with values. To populate the fields with values, the direct action
API 116 can ping, poll or otherwise obtain information from one or
more sensors 134 of the computing device 206 or a user interface of
the device 206. For example, the direct action API 116 can detect
the source location using a location sensor, such as a GPS sensor.
The direct action API 116 can obtain further information by
submitting a survey, prompt, or query to the end of user of the
computing device 206. The direct action API can submit the survey,
prompt, or query via interface 170 of the data processing system
102 and a user interface of the computing device 206 (e.g., audio
interface, voice-based user interface, display, or touch screen).
Thus, the direct action API 116 can select a template for the
action data structure based on the trigger keyword or the request,
populate one or more fields in the template with information
detected by one or more sensors 134 or obtained via a user
interface, and generate, create or otherwise construct the action
data structure to facilitate performance of an operation by the
service provider device 210.
[0063] The data processing system 102 can select the template based
from the template data structure 132 based on various factors
including, for example, one or more of the trigger keyword,
request, service provider computing device 210, type of service
provider computing device 210, a category that the service provider
computing device 210 falls in (e.g., taxi service, laundry service,
flower service, or food delivery), location, or other sensor
information.
[0064] To select the template based on the trigger keyword, the
data processing system 102 (e.g., via direct action API 116) can
perform a look-up or other query operation on the template database
132 using the trigger keyword to identify a template data structure
that maps or otherwise corresponds to the trigger keyword. For
example, each template in the template database 132 can be
associated with one or more trigger keywords to indicate that the
template is configured to generate an action data structure
responsive to the trigger keyword that the service provider
computing device 210 can process to establish a communication
session.
[0065] In some cases, the data processing system 102 can identify a
service provider computing device 210 based on the trigger keyword.
To identify the service provider computing device 210 based on the
trigger keyword, the data processing system 102 can perform a
lookup in the data repository 124 to identify a service provider
computing device 210 that maps to the trigger keyword. For example,
if the trigger keyword includes "ride" or "to go to", then the data
processing system 102 (e.g., via direct action API 116) can
identify the service provider computing device 210 as corresponding
to Taxi Service Company A. The data processing system 102 can
select the template from the template database 132 using the
identify service provider computing device 210. For example, the
template database 132 can include a mapping or correlation between
service provider computing device 210 or entities to templates
configured to generate an action data structure responsive to the
trigger keyword that the service provider computing device 210 can
process to establish a communication session. In some cases, the
template can be customized for the service provider computing
device 210 or for a category of service provider computing device
210. The data processing system 102 can generate the action data
structure based on the template for the service provider computing
device 210.
[0066] To construct or generate the action data structure, the data
processing system 102 can identify one or more fields in the
selected template to populate with values. The fields can be
populated with numerical values, character strings, Unicode values,
Boolean logic, binary values, hexadecimal values, identifiers,
location coordinates, geographic areas, timestamps, or other
values. The fields or the data structure itself can be encrypted or
masked to maintain data security.
[0067] Upon determining the fields in the template, the data
processing system 102 can identify the values for the fields to
populate the fields of the template to create the action data
structure. The data processing system 102 can obtain, retrieve,
determine or otherwise identify the values for the fields by
performing a look-up or other query operation on the data
repository 124.
[0068] In some cases, the data processing system 102 can determine
that the information or values for the fields are absent from the
data repository 124. The data processing system 102 can determine
that the information or values stored in the data repository 124
are out-of-date, stale, or otherwise not suitable for the purpose
of constructing the action data structure responsive to the trigger
keyword and request identified by the NLP component 171 (e.g., the
location of the client computing device 206 may be the old location
and not be the current location; an account can be expired; the
destination restaurant may have moved to a new location; physical
activity information; or mode of transportation).
[0069] If the data processing system 102 determines that it does
not currently have access, in memory of the data processing system
102, to the values or information for the field of the template,
the data processing system 102 can acquire the values or
information. The data processing system 102 can acquire or obtain
the information by querying or polling one or more available
sensors of the client computing device 206, prompting the end user
of the client computing device 206 for the information, or
accessing an online web-based resource using an HTTP protocol. For
example, the data processing system 102 can determine that it does
not have the current location of the client computing device 206,
which may be a needed field of the template. The data processing
system 102 can query the client computing device 206 for the
location information. The data processing system 102 can request
the client computing device 206 to provide the location information
using one or more location sensors 134, such as a Global
Positioning System sensor, WIFI triangulation, cell tower
triangulation, Bluetooth beacons, IP address, or other location
sensing technique.
[0070] The direct action API 116 can transmit the action data
structure to a third-party provider device (e.g., service provider
device 210) to cause the service provider computing device 210 to
invoke a conversational application programming interface (e.g.,
service provider NLP component 142) and establish a communication
session between the service provider computing device 210 and the
client computing device 206. Responsive to establishing the
communication session between the service provider device 210 and
the client computing device 206, the service provider device 210
can transmit data packets directly to the client computing device
206 via network 105. In some cases, the service provider device 210
can transmit data packets to the client computing device 206 via
data processing system 102 and network 105.
[0071] In some cases, the service provider computing device 210 can
execute at least a portion of the conversational API 142. For
example, the service provider computing device 210 can handle
certain aspects of the communication session or types of queries.
The service provider computing device 210 may leverage the NLP
component 171 executed by the data processing system 102 to
facilitate processing the audio signals associated with the
communication session and generating responses to queries. In some
cases, the data processing system 102 can include the
conversational API 142 configured for the service provider
computing device 210. In some cases, the data processing system
routes data packets between the client computing device and the
third-party provider device to establish the communication session.
The data processing system 102 can receive, from the service
provider computing device 210, an indication that the third-party
provider device established the communication session with the
client device 206. The indication can include an identifier of the
client computing device 206, timestamp corresponding to when the
communication session was established, or other information
associated with the communication session, such as the action data
structure associated with the communication session.
[0072] In some cases, the conversational API can be a second NLP
that includes one or more component or function of the first NLP
171. The second NLP 142 can interact or leverage the first NLP 171.
In some cases, the system 100 can include a single NLP 171 executed
by the data processing system 102. The single NLP 171 can support
both the data processing system 102 and the service provider
computing device 210. In some cases, the direct action API 116
generates or constructs an action data structure to facilitate
performing a service, and the conversational API generates
responses or queries to further a communication session with an end
user or obtain additional information to improve or enhance the end
user's experience or performance of the service.
[0073] The data processing system 102 can include, execute, access,
or otherwise communicate with a session handler component 114 to
establish a communication session between the client device 206 and
the data processing system 102. The communication session can refer
to one or more data transmissions between the client device 206 and
the data processing system 102 that includes the input audio signal
that is detected by a sensor 134 of the client device 206, and the
output signal transmitted by the data processing system 102 to the
client device 206. The data processing system 102 (e.g., via the
session handler component 114) can establish the communication
session responsive to receiving the input audio signal. The data
processing system 102 can set a duration for the communication
session. The data processing system 102 can set a timer or a
counter for the duration set for the communication session.
Responsive to expiration of the timer, the data processing system
102 can terminate the communication session.
[0074] The communication session can refer to a network-based
communication session in which the client device 206 provides
authenticating information or credentials to establish the session.
In some cases, the communication session refers to a topic or a
context of audio signals carried by data packets during the
session. For example, a first communication session can refer to
audio signals transmitted between the client device 206 and the
data processing system 102 that are related to (e.g., include
keywords, action data structures, or content item objects) a taxi
service; and a second communication session can refer to audio
signals transmitted between the client device 206 and data
processing system 102 that are related to a laundry and dry
cleaning service. In this example, the data processing system 102
can determine that the context of the audio signals are different
(e.g., via the NLP component 171), and separate the two sets of
audio signals into different communication sessions. The session
handler 114 can terminate the first session related to the ride
service responsive to identifying one or more audio signals related
to the dry cleaning and laundry service. Thus, the data processing
system 102 can initiate or establish the second session for the
audio signals related to the dry cleaning and laundry service
responsive to detecting the context of the audio signals.
[0075] The data processing system 102 can include, execute, or
otherwise communicate with a content selector component 118 to
receive the trigger keyword identified by the natural language
processor and select, based on the trigger keyword, a content item
via a real-time content selection process. The content selection
process can refer to, or include, selecting sponsored content item
objects provided by third-party content providers 106. The
real-time content selection process can include a service in which
content items provided by multiple content providers are parsed,
processed, weighted, or matched in order to select one or more
content items to provide to the computing device 206. The content
selector component 118 can perform the content selection process in
real-time. Performing the content selection process in real-time
can refer to performing the content selection process responsive to
the request for content received via the client computing device
206. The real-time content selection process can be performed
(e.g., initiated or completed) within a time interval of receiving
the request (e.g., 5 seconds, 10 seconds, 20 seconds, 30 seconds, 1
minute, 2 minutes, 3 minutes, 5 minutes, 10 minutes, or 20
minutes). The real-time content selection process can be performed
during a communication session with the client computing device
206, or within a time interval after the communication session is
terminated.
[0076] For example, the data processing system 102 can include a
content selector component 118 designed, constructed, configured or
operational to select content item objects. To select content items
for display in a voice-based environment, the data processing
system 102 (e.g., via NLP component 171) can parse the input audio
signal to identify keywords (e.g., a trigger keyword), and use the
keywords to select a matching content item based on a broad match,
exact match, or phrase match. For example, the content selector
component 118 can analyze, parse, or otherwise process subject
matter of candidate content items to determine whether the subject
matter of the candidate content items correspond to the subject
matter of the keywords or phrases of the input audio signal
detected by the microphone of the client computing device 206. The
content selector component 118 may identify, analyze, or recognize
voice, audio, terms, characters, text, symbols, or images of the
candidate content items using an image processing technique,
character recognition technique, natural language processing
technique, or database lookup. The candidate content items may
include metadata indicative of the subject matter of the candidate
content items, in which case the content selector component 118 may
process the metadata to determine whether the subject matter of the
candidate content item corresponds to the input audio signal.
[0077] Content providers 106 may provide additional indicators when
setting up a content campaign that includes content items. The
content provider 106 may provide information at the content
campaign or content group level that the content selector component
118 may identify by performing a lookup using information about the
candidate content item. For example, the candidate content item may
include a unique identifier, which may map to a content group,
content campaign, or content provider. The content selector
component 118 may determine, based on information stored in content
campaign data structure in data repository 124, information about
the content provider 106.
[0078] The data processing system 102 can receive, via a computer
network, a request for content for presentation on a computing
device 206. The data processing system 102 can identify the request
by processing an input audio signal detected by a microphone of the
client computing device 206. The request can include selection
criteria of the request, such as the device type, location, and a
keyword associated with the request. The request can include the
action data structure or action data structure.
[0079] Responsive to the request, the data processing system 102
can select a content item object from data repository 124 or a
database associated with the content provider 106, and provide the
content item for presentation via the computing device 206 via
network 105. The content item object can be provided by a content
provider computing device 222 different from the service provider
device 210. The content item can correspond to a type of service
different from a type of service of the action data structure
(e.g., taxi service versus food delivery service). The computing
device 206 can interact with the content item object. The computing
device 206 can receive an audio response to the content item. The
computing device 206 can receive an indication to select a
hyperlink or other button associated with the content item object
that causes or allows the computing device 206 to identify service
provider 210, request a service from the service provider 210,
instruct the service provider 210 to perform a service, transmit
information to the service provider 210, or otherwise query the
service provider device 210.
[0080] The data processing system 102 can include, execute, or
communicate with an audio signal generator component 122 to
generate an output signal. The output signal can include one or
more portions. For example, the output signal can include a first
portion and a second portion. The first portion of the output
signal can correspond to the action data structure. The second
portion of the output signal can correspond to the content item
selected by the content selector component 118 during the real-time
content selection process.
[0081] The audio signal generator component 122 can generate the
output signal with a first portion having sound corresponding to
the first data structure. For example, the audio signal generator
component 122 can generate the first portion of the output signal
based on one or more values populated into the fields of the action
data structure by the direct action API 116. In a taxi service
example, the values for the fields can include, for example, 123
Main Street for pick-up location, 1234 Main Street for destination
location, 2 for number of passengers, and economy for the level of
service. The audio signal generator component 122 can generate the
first portion of the output signal in order to confirm that the end
user of the computing device 206 wants to proceed with transmitting
the request to the service provider 210. The first portion can
include the following output "Would you like to order an economy
car from taxi service provider A to pick two people up at 123 Main
Street and drop off at 1234 Main Street?"
[0082] In some cases, the first portion can include information
received from the service provider device 210. The information
received from service provider device 210 can be customized or
tailored for the action data structure. For example, the data
processing system 102 (e.g., via direct action API 116) can
transmit the action data structure to the service provider 210
before instructing the service provider 210 to perform the
operation. Instead, the data processing system 102 can instruct the
service provider device 210 to perform initial or preliminary
processing on the action data structure to generate preliminary
information about the operation. In the example of the taxi
service, the preliminary processing on the action data structure
can include identifying available taxis that meet the level of
service requirement that are located around the pick-up location,
estimating an amount of time for the nearest available taxi to
reach the pick-up location, estimating a time of arrival at the
destination, and estimating a price for the taxi service. The
estimated preliminary values may include a fixed value, an estimate
that is subject to change based on various conditions, or a range
of values. The service provider device 210 can return the
preliminary information to the data processing system 102 or
directly to the client computing device 206 via the network 105.
The data processing system 102 can incorporate the preliminary
results from the service provider device 210 into the output
signal, and transmit the output signal to the computing device 206.
The output signal can include, for example, "Taxi Service Company A
can pick you up at 123 Main Street in 10 minutes, and drop you off
at 1234 Main Street by 9 AM for $10. Do you want to order this
ride?" This can form the first portion of the output signal.
[0083] In some cases, the data processing system 102 can form a
second portion of the output signal. The second portion of the
output signal can include a content item selected by the content
selector component 118 during a real-time content selection
process. The first portion can be different from the second
portion. For example, the first portion can include information
corresponding to the action data structure that is directly
responsive to the data packets carrying the input audio signal
detected by the sensor 134 of the client computing device 206,
whereas the second potion can include a content item selected by a
content selector component 118 that can be tangentially relevant to
the action data structure, or include sponsored content provided by
a content provider device 106. For example, the end user of the
computing device 206 can request a taxi from Taxi Service Company
A. The data processing system 102 can generate the first portion of
the output signal to include information about the taxi from the
Taxi Service Company A. However, the data processing system 102 can
generate the second portion of the output signal to include a
content item selected based on the keywords "taxi service" and
information contained in the action data structure that the end
user may be interested in. For example, the second portion can
include a content item or information provided by a different taxi
service company, such as Taxi Service Company B. While the user may
not have specifically requested Taxi Service Company B, the data
processing system 102 may nonetheless provide a content item from
Taxi Service Company B because the user may choose to perform an
operation with Taxi Service Company B.
[0084] The data processing system 102 can transmit information from
the action data structure to the Taxi Service Company B to
determine a pick-up time, time of arrival at the destination, and a
price for the ride. The data processing system 102 can receive this
information and generate the second portion of the output signal as
follows: "Taxi Service Company B can pick you up at 123 Main Street
in 2 minutes, and drop you off at 1234 Main Street by 8:52 AM for
$15. Do you want this ride instead?" The end user of computing
device 206 can then select the ride provided by Taxi Service
Company A or the ride provided by Taxi Service Company B.
[0085] Prior to providing, in the second portion of the output
signal, the sponsored content item corresponding to the service
provided by Taxi Service Company B, the data processing system 102
can notify the end user computing device that the second portion
corresponds to a content item object selected during a real-time
content selection process (e.g., by the content selector component
118). However, the data processing system 102 can have limited
access to different types of interfaces to provide the notification
to the end user of the computing device 206. For example, the
computing device 206 may not include a display device, or the
display device may be disabled or turned off. The display device of
the computing device 206 may consume greater resources than the
speaker of the computing device 206, so it may be less efficient to
turn on the display device of the computing device 206 as compared
to using the speaker of the computing device 206 to convey the
notification. Thus, in some cases, the data processing system 102
can improve the efficiency and effectiveness of information
transmission over one or more interfaces or one or more types of
computer networks. For example, the data processing system 102
(e.g., via the audio signal generator component 122) can module the
portion of the output audio signal comprising the content item to
provide the indication or notification the end user that that
portion of the output signal comprises the sponsored content
item.
[0086] The data processing system 102 (e.g., via interface 170 and
network 105) can transmit data packets comprising the output signal
generated by the audio signal generator component 122. The output
signal can cause the audio driver component 138 of or executed by
the client device 206 to drive a speaker (e.g., transducer 136) of
the client device 206 to generate an acoustic wave corresponding to
the output signal.
[0087] FIG. 2 is a block diagram of an example system 100 in which
a data processing system 102 manages digital component distribution
services. The example system 100 includes one or more networks 105,
such as a local area network (LAN), a wide area network (WAN), the
Internet, or a combination thereof. The network 105 connects user
devices 206, websites 208, service provider computing devices 210,
and the data processing system 102. The system 100 may include many
thousands of user devices 206, websites 208, and service provider
computing devices 210.
[0088] A website 208 is one or more resources 212 associated with a
domain name and hosted by one or more servers. An example website
is a collection of webpages formatted in hypertext markup language
(HTML) that can contain text, images, multimedia content, and
programming elements, such as scripts. Each website 208 is
maintained by a content provider computing device 222, which is an
entity that controls, manages and/or owns the website 208.
[0089] A resource 212 is any data that can be provided over the
network 105. A resource 212 is identified by a resource address
that is associated with the resource 212. Resources include HTML
pages, word processing documents, and portable document format
(PDF) documents, images, video, and feed sources, to name only a
few. The resources can include content, such as words, phrases,
images and sounds, that may include embedded information (such as
meta-information in hyperlinks) and/or embedded instructions (such
as JavaScript scripts).
[0090] A user device 206 is an electronic device that is under
control of a user and is capable of requesting and receiving
resources over the network 105. Example user devices 206 include
personal computers, mobile communication devices, and other devices
that can send and receive data over the network 105. A user device
206 typically includes a user application, such as a web browser,
to facilitate the sending and receiving of data over the network
105. User devices 206, such as mobile communication devices, may
also include other user applications, such as text message
applications, gaming applications, news applications, book and
magazine reader applications, and other applications provided by
content provider computing devices 222. Applications provided by
content provider computing devices 222 may also be known as
resources.
[0091] A user device 206 can request resources 212 from a website
208. In turn, data representing the resource 212 can be provided to
the user device 206 for presentation by the user device 206. The
data representing the resource 212 can also include data specifying
a portion of the resource or a portion of a user display (e.g., a
presentation location of a pop-up window or in a slot of a webpage)
in which digital components can be presented. These specified
portions of the resource or user display are referred to as digital
component slots.
[0092] To facilitate searching of these resources, the environment
can include a search system 214 that identifies the resources by
crawling and indexing the resources provided by the content
provider computing devices on the websites 208. Data about the
resources can be indexed based on the resource to which the data
corresponds. The indexed and, optionally, cached copies of the
resources are stored in an indexed cache 216.
[0093] User devices 206 can submit search queries 220 to the search
system 214 over the network 105. In response, the search system 214
accesses the indexed cache 216 to identify resources that are
relevant to the search query 220. The search system 214 identifies
the resources in the form of search results 218 and returns the
search results 218 to the user devices 206 in search results pages.
A search result 218 is data generated by the search system 214 that
identifies a resource that is responsive to a particular search
query, and includes a link to the resource. An example search
result 218 can include webpage title, a snippet of text or a
portion of an image extracted from the webpage, and the URL of the
webpage. Search results pages can also include one or more digital
component slots in which digital components can be presented.
[0094] When a resource 212 provided by a content provider computing
device 222 or search results 218 are requested by a user device
206, the data processing system 102 receives a request for digital
components to be provided with the resource 212, from a content
provider computing device 222, or search results 218. The request
for digital components can include characteristics of the digital
component slots that are defined for the requested resource or
search results page, and can be provided to the data processing
system 102.
[0095] For example, a reference (e.g., URL) to the resource for
which the digital component slot is defined, a size of the digital
component slot, and/or media types that are available for
presentation in the digital component slot can be provided to the
data processing system 102. Similarly, keywords associated with a
requested resource ("resource keywords") or a search query 220 for
which search results are requested can also be provided to the data
processing system 102 to facilitate identification of digital
components that are relevant to the resource or search query 220.
Further, images and multimedia elements that are associated with
the resource may be provided to the data processing system 102.
[0096] Based on data included in the request for digital
components, the data processing system 102 can select digital
components that are eligible to be provided in response to the
request ("eligible digital components"). For example, eligible
digital components can include digital components having
characteristics matching the characteristics of digital component
slots and that are identified as relevant to specified resource
keywords or search queries 220. In some implementations, digital
components having targeting keywords that match the resource
keywords or the search query 220 are selected as eligible digital
components by the data processing system 102. As described with
respect to embodiments, digital components associated with digital
component images with features matching images associated with a
resource or webpage may be selected as eligible digital components
by the data processing system 102.
[0097] A targeting keyword can match a resource keyword or a search
query 220 by having the same textual content ("text") as the
resource keyword or search query 220. For example, a digital
component associated with the targeting keyword "daisy" can be an
eligible digital component for a digital component request
including the resource keyword "daisy." Similarly, the digital
component can be selected as an eligible digital component for a
digital component request including the search query "daisy."
[0098] A targeting keyword can also match a resource keyword or a
search query 220 by having text that is identified as being
relevant to a targeting keyword or search query 220 despite having
different text than the targeting keyword. For example, a digital
component having the targeting keyword "daisy" may also be selected
as an eligible digital component for a digital component request
including a resource keyword or search query for "flowers" because
daisy is a type of flower, and therefore, is likely to be relevant
to the term "flowers."
[0099] As described herein with reference to embodiments, the
digital component system can use features of multimedia elements
provided in the request for digital components from the content
provider computing device to identify relevant digital components.
The digital component system may also use text labels associated
with multimedia elements provided in the request for digital
components to identify relevant digital components.
[0100] Search system 214 may provide functionality to users
including image search functionality, audio search functionality,
and video search functionality. A user may search for images by
entering a search query 220 including one or more keywords. For
example, the user may enter the search query "handbag" and be
presented with a selection of one or more images of handbags or
purses. Upon selecting an image, the image may then be associated
with the search query term "handbag" as the text label for that
image. The image may be provided as part of a content provider
computing device webpage. Accordingly, the digital component system
may use this text label to identify relevant digital components in
response to a request for digital components.
[0101] Similarly, a user may search for audio content or video
content by entering a search query 220 including one or more
keywords. For example, the user may enter the search query "sports
car" and be presented with a selection of one or more videos of
sports cars or race cars. Upon selecting a video, the video may
then be associated with the search query term "sports car" as the
text label for that video. The video may be provided as part of a
content provider computing device webpage. Accordingly, the digital
component system may use this text label to identify relevant
digital components in response to a request for digital
components.
[0102] The data processing system 102 can select the eligible
digital components that are provided for presentation in digital
component slots of a resource based on results of an auction. For
example, the data processing system 102 can receive bids from
service provider computing devices and allocate the digital
component slots to the highest bidders at the conclusion of the
auction. The bids are amounts that the service provider computing
devices are willing to pay for presentation (or selection) of their
digital component with a resource or search results page. For
example, a bid can specify an amount that a service provider
computing device is willing to pay for each 1000 impressions (i.e.,
presentations) of the digital component, referred to as a CPM bid.
Alternatively, the bid can specify an amount that the service
provider computing device is willing to pay for a selection (i.e.,
a click-through) of the digital component or a "conversion"
following selection of the digital component. The highest bidders
can be determined based on the bids alone, or based on the bids of
each bidder being multiplied by one or more factors, such as
quality scores derived from digital component performance, landing
page scores, and the like.
[0103] Service Provider Computing Devices can also specify budgets
for their digital component campaigns. A budget is a specified
amount that a service provider computing device is willing to pay
for distribution of content over a specified budget period. The
specified period can be, for example, a specified time (e.g., one
day, one week, or one year), a specified number of events (e.g., a
number of impressions or clicks), or some other delineation of time
or events. Once the amount the service provider computing device is
charged for distribution of content during the budget period
matches or exceeds the budget amount, the campaign can be prevented
from providing content for the remainder of the budget period
unless the service provider computing device increases or overrides
its specified budget.
[0104] A conversion occurs when a user performs a particular action
related to a digital component provided with a resource or search
results page. What constitutes a conversion may vary from case to
case and can be determined in a variety of ways. For example, a
conversion may occur when a user clicks on a digital component, is
referred to a webpage, and consummates a purchase there before
leaving that webpage. A conversion can also be defined by a service
provider computing device to be any measurable/observable user
action such as, for example, downloading a white paper, navigating
to at least a given depth of a website, viewing at least a certain
number of webpages, spending at least a predetermined amount of
time on a website or webpage, or registering on a website. Other
actions that constitute a conversion can also be used.
[0105] In one embodiment, digital components may be computer
display digital components. a service provider computing device 210
may provide data associated with one or more digital components,
such as a service provider computing device name, text to be
included in a digital component, keywords, and other information.
The data processing system 102 may generate computer display
digital components based on the received data. For example, the
data processing system 102 may combine the received data into a
creative for the digital component, and generate a computer display
digital component responsive to the keywords specified by the
service provider computing device. In another embodiment, computer
display digital components may be provided by service provider
computing devices 210.
[0106] In embodiments, data processing system 102 (and its
recognition engine 104) may be implemented in software, firmware,
hardware or any combination thereof on one or more computing
devices. For example, data processing system 102 may be part of or
may be implemented with a computing device, such as, a
processor-based computing device. A computing device can be any
type of device having one or more processors. For example, a
computing device can be a workstation, mobile device (e.g., a
mobile phone, personal digital assistant, tablet or laptop),
computer, server, compute cluster, server farm, game console,
set-top box, kiosk, embedded system or other device having at least
one processor and memory. Embodiments may be software executed by a
processor, firmware, hardware or any combination thereof in a
computing device.
[0107] Examples of providing image digital components based on the
content of a resource are described with reference to FIGS. 3-5. A
system that can be used to implement these examples is then
described with reference to FIG. 6.
[0108] FIG. 3 illustrates an exemplary method 300 for providing
computer display digital components based on multimedia element
content of a resource, according to an embodiment. The process 300
can be implemented, for example, by the recognition engine 104
and/or the data processing system 102 of FIG. 2. In some
implementations, the recognition engine 104 is a data processing
apparatus that includes one or more processors that are configured
to perform actions of the process 300. In other implementations, a
computer readable medium can include instructions that when
executed by a computer cause the computer to perform actions of the
process 300.
[0109] In step 302, a request for digital components for a content
provider computing device resource is received. The request for
digital components may be received in response to a user requesting
a content provider computing device webpage from the content
provider computing device, or requesting a resource from a content
provider computing device such as an application. The request for
digital components may include one or more multimedia elements
displayed on the content provider computing device resource, as
well as keywords associated with the content of the content
provider computing device resource.
[0110] In step 304, one or more multimedia elements displayed on
the resource are identified. Further, features of each of the one
or more multimedia elements may be extracted. Multimedia elements
may include, but are not limited to, images, audio data, video
data, animation data, interactive elements of the resource, or
other data that may be included on a content provider computing
device resource. Feature extraction is further described below.
[0111] In step 306, a digital component associated with a digital
component multimedia element is identified. As described with
reference to step 304, digital component multimedia elements may
include, but are not limited to, image, audio data, video data,
animation data, interactive elements, or other data. The digital
component can be identified by matching features of the digital
component multimedia element with features of the one on more
multimedia elements displayed on the resource. For example, if the
multimedia element is an image, one or more edges, corner features,
line features, interest points, blobs, regions of interest, or
ridges in an image displayed on the content provider computing
device resource may match one or more of such features in a digital
component image. Based on this matching, the digital component
associated with the digital component image may be identified.
[0112] In one embodiment, features may be extracted from the images
displayed on the content provider computing device's resource using
a feature detection technique. Features may include, but are not
limited to, edges, corner features, interest points, blobs or
regions of interest, or ridges. Feature detection techniques may
include, but are not limited to, canny edge detection,
scale-invariant feature transform (SIFT), speeded up robust feature
(SURF), and other known feature detection techniques. Further, in
one embodiment, features may be extracted from digital component
images when a digital component with an associated digital
component image is provided by a service provider computing device,
such that the features can be matched in response to a request for
digital components.
[0113] In one embodiment, a digital component may be identified if
the number of features that match between an image on a content
provider computing device resource and a digital component image
meets a threshold. For example, a digital component may be
identified only if five or more features match between a digital
component image associated with the digital component and an image
on the content provider computing device resource. Defining such a
threshold may, increase the likelihood that the identified digital
component corresponds to the image content of the content provider
computing device resource.
[0114] In one embodiment, features of the multimedia elements
displayed on the content provider computing device's resource may
include text label data. As described above, when a user performs a
query for images, video, audio, or other content, the query terms
that result in the multimedia element may be associated with the
multimedia element after the user selects or clicks on the
multimedia element. The query terms may become text label data
associated with the multimedia element.
[0115] In one embodiment, features of audio data included on a
content provider computing device resource may be matched with
features of audio data associated with a digital component. For
example, features of the audio data included on the content
provider computing device resource may be matched with features of
audio data associated with a digital component by using audio
search technique. Such a technique may extract a feature, such as a
unique fingerprint of the audio data included on the content
provider computing device resource, and compare the unique
fingerprint to a fingerprint of audio data associated with a
digital component. If the unique fingerprint matches the
fingerprint of audio data associated with a digital component in
part or in whole; the digital component associated with the audio
data may be identified.
[0116] In one embodiment, features of video data included on a
content provider computing device resource may be matched with
features of video data associated with a digital component. For
example, features of video data included on the content provider
computing device resource may be extracted and matched with
features of video data associated with a digital component, using a
video matching technique. Such a technique may extract individual
still frames of each video and compare the still frames to
determine whether a video on a content provider computing device
resource matches a video associated with a digital component. If a
threshold number of frames matches between the videos, the digital
component associated with the video may be identified. Similarly,
image matching techniques as described herein may match individual
flames of video data associated with a digital component to images
displayed on a content provider computing device resource. If
edges, corner features, or other features of the individual frames
of video data are associated with a digital component that match
features in the image displayed on the content provider computing
device resource, the digital component may be identified.
[0117] In one embodiment, the format of the digital component
multimedia element is the same as the format of the multimedia
element displayed on the content provider computing device
resource. For example, a digital component associated with a video
as its digital component multimedia element may be identified in
response to a request for digital components from a content
provider computing device resource displaying a video. In another
embodiment, the format of the digital component multimedia element
is different than the format of the multimedia element displayed on
the content provider computing device resource. Thus, for example,
a digital component associated with an image of shoes as its
digital component multimedia element may be identified in response
to a request for digital components from a content provider
computing device resource displaying a video of sports players
wearing the same or similar shoes. Such a digital component may be
identified using image matching techniques as described above.
[0118] In step 308, the digital component is provided to the
content provider computing device associated with the content
provider computing device resource. The digital component may be
provided over a computer network to the content provider computing
device. The digital component may then be displayed on the content
provider computing device resource along with the content of the
content provider computing device resource,
[0119] FIG. 4 illustrates a further exemplary method 400 for
providing computer display digital components based on multimedia
content of a resource, according to an embodiment.
[0120] In step 402, a request for digital components for a content
provider computing device resource is received. The request for
digital components may be received in response to a user requesting
a content provider computing device resource from the content
provider computing device, or requesting a resource from a content
provider computing device such as an application, and may include
one or more multimedia elements displayed on the content provider
computing device resource or other content of the content provider
computing device resource.
[0121] In step 404, text label data associated with each of the one
or more multimedia elements is identified. As described above,
query terms associated with a multimedia element may be used as
text label data for the multimedia element. Text label data may
further be a label associated with the multimedia element which
describes the multimedia element. For example, metadata or data
associated with the image may be used as text label data. For
example, the "alt" or "title" attribute of an HTML, image tag may
allow a content provider computing device to specify text that is
displayed instead of an image or along with an image. Text included
in the "alt" attribute may be used to find relevant digital
components.
[0122] In step 406, a digital component associated with a keyword
responsive to the text label data is identified. The digital
component can be identified by matching text label data of the
multimedia element displayed on the content provider computing
device resource to keywords of a digital component. For example,
the digital component may be associated with a keyword that exactly
matches the text label data. Additionally, the digital component
may be associated with a keyword related to the text label
data.
[0123] In step 408, the digital component is provided to a content
provider computing device associated with the content provider
computing device resource. The digital component may then be
displayed on the content provider computing device resource along
with the content of the content provider computing device
resource.
[0124] In one embodiment, the content provider computing device
associated with the content provider computing device resource is
compensated for displaying the digital component. For example, the
content provider computing device associated with the content
provider computing device resource may be compensated an amount
corresponding to the bid amount of the provided digital
component.
[0125] According to an embodiment, steps 302, 304, 306, and 308 may
be performed by the recognition engine 104. Further, steps 402,
404, 406 and 408 may be performed by the recognition engine
104.
[0126] FIG. 5 is a swim lane diagram illustrating a process for
providing computer display digital components responsive to image
content. In box 502, a data processing system 102 receives computer
display digital components and bids. Each computer display digital
component may be associated with a digital component multimedia
element.
[0127] In box 504, a user device requests a resource, such as a
webpage. A content provider computing device 222 may receive the
request in box 506 and in response may transmit a request for
digital components to data processing system 102 in box 508. The
request may include multimedia elements displayed on the content
provider computing device webpage. In box 510, the data processing
system 102 receives the request for digital components, and in box
512, the data processing system 102 identifies features of
multimedia elements displayed on the content provider computing
device webpage, as described herein.
[0128] In box 514, the digital component may match identified
features to features of digital component multimedia elements
received in box 502. Based on matching features, in box 516, a
computer display digital component may be identified by data
processing system 102. The data processing system 102 may then
transmit the computer display digital component to content provider
computing device 222 in box 518.
[0129] In box 520, the content provider computing device may
receive the computer display digital component, which may then be
displayed on the requested webpage in box 522 for presentation to
the user device.
[0130] FIG. 6 illustrates an example computer system 600 in which
embodiments, or portions thereof; may be implemented as
computer-readable code. For example, data processing system 102 may
be implemented in computer system 600 using hardware, software,
firmware, tangible computer-readable media having instructions
stored thereon, or a combination thereof and may be implemented in
one or more computer systems or other processing systems. Hardware,
software, or any combination of such may embody any of the modules
and components in the systems described herein.
[0131] If programmable logic is used, such logic may execute on a
commercially available processing platform or a special purpose
device. One of ordinary skill in the art may appreciate that
embodiments of the disclosed subject matter can be practiced with
various computer system configurations, including multi-core
multiprocessor systems, minicomputers, mainframe computers,
computers linked or clustered with distributed functions, as well
as pervasive or miniature computers that may be embedded into
virtually any device.
[0132] For instance, a computing device having at least one
processor device and a memory may be used to implement the
above-described embodiments. A processor device may be a single
processor, a plurality of processors, or combinations thereof.
Processor devices may have one or more processor "cores."
[0133] Various embodiments of the invention are described in terms
of this example computer system 600. After reading this
description, it will become apparent to a person skilled in the
relevant art how to implement the invention using other computer
systems and/or computer architectures. Although operations may be
described as a sequential process, some of the operations may in
fact be performed in parallel, concurrently, and/or in a
distributed environment, and with program code stored locally or
-remotely for access by single or multi-processor machines. In
addition, in some embodiments the order of operations may be
rearranged without departing from the spirit of the disclosed
subject matter.
[0134] Processor device 604 may be a special purpose or a
general-purpose processor device. As will be appreciated by persons
skilled in the relevant art, processor device 604 may also be a
single processor in a multi-core/multiprocessor system, such system
operating alone, or in a cluster of computing devices operating in
a cluster or server farm. Processor device 604 is connected to a
communication infrastructure 606, for example, a bus, message
queue, network, or multi-core message-passing scheme.
[0135] Computer system 600 also includes a main memory 608, for
example, random access memory (RAM), and may also include a
secondary memory 610. Secondary memory 610 may include, for
example, a hard disk drive 612, or a removable storage drive 614.
Removable storage drive 614 may comprise a floppy disk drive, a
magnetic tape drive, an optical disk drive, a flash memory, or the
like. The removable storage drive 614 reads from and/or writes to a
removable storage unit 618 in a well-known manner. Removable
storage unit 618 may comprise a floppy disk, magnetic tape, optical
disk, etc. which is read by and written to by removable storage
drive 618. As will be appreciated by persons skilled in the
relevant art, removable storage unit 618 includes a
computer-readable storage medium having stored therein computer
software and/or data.
[0136] In alternative implementations, secondary memory 610 may
include other similar means for allowing computer programs or other
instructions to be loaded into computer system 600. Such means may
include, for example, a removable storage unit 622 and an interface
620. Examples of such means may include a program cartridge and
cartridge interface such as that found in video game devices), a
removable memory chip (such as an EPROM, or PROM) and associated
socket, and other removable storage units 622 and interfaces 620
which allow software and data to be transferred from the removable
storage unit 622 to computer system 600.
[0137] Computer system 600 may also include a communications
interface 624. Communications interface 624 allows software and
data to be transferred between computer system 600 and external
devices. Communications interface 624 may include a modem, a
network interface (such as an Ethernet card), a communications
port, a PCMCIA slot and card, or the like. Software and data
transferred via communications interface 624 may be in the form of
signals, which may be electronic, electromagnetic, optical, or
other signals capable of being received by communications interface
624. These signals may be provided to communications interface 624
via a communications path 626. Communications path 626 carries
signals and may be implemented using wire or cable, fiber optics, a
phone line, a cellular phone link, an RFC link or other
communications channels.
[0138] In this document, the terms "computer program medium" and
"computer-readable medium" are used to generally refer to media
such as removable storage unit 618, removable storage unit 622, and
a hard disk installed in hard disk drive 612. Computer program
medium and computer-readable medium may also refer to memories,
such as main memory 608 and secondary memory 610, which may be
memory semiconductors (e.g. DRAMs, etc.).
[0139] Computer programs (also called computer control logic) are
stored in main memory 608 and/or secondary memory 610. Computer
programs may also be received via communications interface 624.
Such computer programs, when executed, enable computer system 600
to implement the present invention as discussed herein. In
particular, the computer programs, when executed, enable processor
device 604 to implement the processes of the present invention,
such as the stages in the method illustrated by flowchart 300 of
FIG. 3 or flowchart 400 of FIG. 4 discussed above. Accordingly,
such computer programs represent controllers of the computer system
600. Where the invention is implemented using software, the
software may be stored in a computer program product and loaded
into computer system 600 using removable storage drive 614,
interface 620, and hard disk drive 612, or communications interface
624.
[0140] Embodiments also may be directed to computer program
products comprising software stored on any computer-readable
medium. Such software, when executed in one or more data processing
device, causes a data processing device(s) to operate as described
herein. Embodiments employ any computer useable or readable medium.
Examples of tangible computer-readable mediums include, but are not
limited to, primary storage devices (e.g., any type of random
access memory), secondary storage devices (e.g., hard drives,
floppy disks, CD ROMS, ZIP disks, tapes, magnetic storage devices,
and optical storage devices, MEMS, nanotechnological storage
device, etc.).
[0141] FIG. 7 is an illustration of the system 100 to route
packetized actions via a computer network. The system can include
one or more component of system 100 depicted in FIG. 1C. At ACT
705, the client computing device 206 can transmit data packets
carrying the input audio signal detected by a microphone or other
sensor of the computing device 206. The client computing device 206
can transmit the input audio signal to the data processing system
102. The data processing system 102 can parse the input audio
signal to identify a keyword, request or other information to
generate an action data structure responsive to the request.
[0142] At ACT 710, the data processing system 102 can transmit the
action data structure to the service provider device 210 (or
service provider computing device 210). The data processing system
102 can transmit the action data structure via a network. The
service provider device 210 can include an interface configured to
receive and process the action data structure transmitted by the
data processing system 102.
[0143] The service provider device 210 (e.g., via a conversational
API) can respond to the action data structure at ACT 715. The
response from the service provider device 210 can include an
indication of a service to perform corresponding to the action data
structure. The response can include a confirmation to proceed with
performing the operation. The response can include a request for
further information to perform the operation corresponding to the
action data structure. For example, the action data structure can
be for a ride, and the service provider 210 can respond with a
request for further information such as a number of passengers for
the ride, a type of car desired by the passenger, desired amenities
in the car, or preferred pick up location. The request for
additional information can include information that may not be
present in the action data structure. For example, the action data
structure can include baseline information to perform the
operation, such as the pick-up location, destination location, and
number of passengers. The baseline information can be the standard
data set used by a plurality of service provider computing devices
210 within the taxi service category. However, a certain taxi
service provider 210 can choose to customize and improve the
operation by requesting additional information or preferences from
the client computing device 206.
[0144] The service provider device 210 can transmit one or more
data packets carrying the response to the data processing system
102 at ACT 715. The data processing system 102 can parse the data
packets and identify a source of the data packets and a destination
for the data packets. At ACT 720, the data processing system 102
can, accordingly, route or forward the data packets to the client
computing device 206. The data processing system 102 can route or
forward the data packets via network 105.
[0145] At ACT 725, the client computing device 206 can transmit an
instruction or command to the data processing system 102 based on
the forwarded response. For example, the response forwarded at 725
can be a request for a number of passengers and a confirmation to
proceed with scheduling the taxi ride. The instruction at 725 can
include the number of passengers and the instruction to proceed
with scheduling the pickup. The client device 206 can transmit one
or more data packets carrying the instruction to the data
processing system 102. The data processing system 102 can route or
forward the data packets carrying the instructions to the service
provider device 210 at ACT 730.
[0146] In some cases, the data processing system 102 can route or
forward the data packets at ACT 720 or ACT 730 as-is (e.g., without
manipulating the data packets). In some cases, the data processing
system 102 can process the data packets to filter out information,
or encapsulate the data packets with information to facilitate
processing of the data packets by the service provider device 210
or the client computing device 206. For example, the data
processing system 102 can mask, hide, or protect the identity of
the client computing device 206 from the service provider device
210. Thus, the data processing system 102 can encrypt identifying
information using a hash function such that the service provider
210 cannot directly identify a device identifier or username of the
client computing device 206. The data processing system 102 can
maintain a mapping of the proxy identifier provided to the service
provider device 210 for use during the communication session to the
identifier or username of the client computing device 206.
[0147] FIG. 8 is an illustration of the system 100 to route
packetized actions via a computer network. The system can include
one or more component of system 100 depicted in FIG. 1C. At 805,
the client computing device 206 can transmit data packets carrying
the input audio signal detected by a microphone or other sensor of
the computing device 206. The client computing device 206 can
transmit the input audio signal to the data processing system 102.
The data processing system 102 can parse the input audio signal to
identify a keyword, request or other information to generate an
action data structure responsive to the request.
[0148] At ACT 810, the data processing system 102 can transmit the
action data structure to the service provider device 210 (or
service provider computing device 210). The data processing system
102 can transmit the action data structure via a network. The
service provider device 210 can include an interface configured to
receive and process the action data structure transmitted by the
data processing system 102.
[0149] The service provider device 210 (e.g., via a conversational
API) can respond to the action data structure at ACT 815. The
response from the service provider device 210 can include an
indication of a service to perform corresponding to the action data
structure. The response can include a confirmation to proceed with
performing the operation. The response can include a request for
further information to perform the operation corresponding to the
action data structure. For example, the action data structure can
be for a ride, and the service provider 210 can respond with a
request for further information such as a number of passengers for
the ride, a type of car desired by the passenger, desired amenities
in the car, or preferred pick up location. The request for
additional information can include information that may not be
present in the action data structure. For example, the action data
structure can include baseline information to perform the
operation, such as the pick-up location, destination location, and
number of passengers. The baseline information can be the standard
data set used by a plurality of service provider computing devices
210 within the taxi service category. However, a certain taxi
service provider 210 can choose to customize and improve the
operation by requesting additional information or preferences from
the client computing device 206.
[0150] The service provider device 210 can transmit one or more
data packets carrying the response directly to the client computing
device 206 via a network 105. For example, instead of routing the
response through the data processing system 102, the service
provider device 210, via a conversational API executed by the
service provider device 210, can respond directly to the client
computing device 206. This can allow the service provider to
customize the communication session.
[0151] At ACT 820, the client computing device 206 can transmit an
instruction or command to service provider device 210 based on the
response. For example, the response provided at 815 can be a
request for a number of passengers and a confirmation to proceed
with scheduling the taxi ride. The instruction at 820 can include
the number of passengers and the instruction to proceed with
scheduling the pickup. The client device 206 can transmit one or
more data packets carrying the instruction to the service provider
device 210 instead of routing the data packets through the data
processing system 102.
[0152] The data processing system 102 can facilitate the service
provider device 210 and the client computing device 206
establishing a communication session independent of the data
processing system 102 by passing communication identifiers to the
respective devices. For example, the data processing system 102 can
forward an identifier of the device 206 to the service provider
computing device 210; and the data processing system 102 can
forward an identifier of the service provider computing device 210
to the device 206. Thus, the service provider computing device 210
can establish the communication session directly with the device
206.
[0153] In some cases, the service provider computing device 210 or
device 206 can separately forward information, such as status
information, about the communication session to the data processing
system 102. For example, the service provider computing device 210
can provide, to the data processing system, an indication that the
service provider computing device 210 successfully established the
communication session with the client device 206.
[0154] FIG. 9 illustrates a block diagram of an example method 900
to extract image features from input requests. The method 900 can
include receiving a first request that includes a first image (ACT
902). The method 900 can include retrieving image data for a
plurality of images (ACT 904). The method 900 can include
extracting an image feature from the first image (ACT 906). The
method 900 can include selecting candidate images (ACT 908). The
method 900 can include selecting a second image from the candidate
images (ACT 910). The method 900 can include transmitting the
second image (ACT 912).
[0155] The method 900 can include receiving a first request that
includes a first image (ACT 902). The first image can be included
in the request. The first image can be captured by a camera
associated with the first computing device. For example, the
computing device can include a built-in camera with which a user
can capture an image. The first request can also include an
audio-based input signal. For example, the audio-based input signal
can be "Ok, what is this?" The audio-based input signal can be
transmitted by the first computing device to the data processing
system 102 with an image the user wants to know more information
about. In some implementations, the NLP component 171 can also
process the first image to determine requests that are associated
with the first image. For example, the NLP component 171 can
analyze a picture of an item and determine the request is to know
where the item can be purchased. The first image can be a video
image. The first image can be a frame or series of frames from a
video input file. The video can be captured at the computing
device.
[0156] The method 900 can also include receiving the request by the
natural language processor component that is executed by the data
processing system 102. The request can be received as a plurality
of packets that are received via a packet based protocol. The
natural language processor component can parse the request identify
a trigger keyword in the request. For example, the request can
include the input audio-signal "Ok, where can I buy this?". The
trigger keyword in this example can be "buy," indicating the user
may want to purchase the item contained in the first image that is
received with the request.
[0157] The method 900 can include retrieving image data for a
plurality of images (ACT 904). The method 900 can include
retrieving the image data for each of the plurality of images. The
method 900 can include retrieving content data from a plurality of
content items. The content items can be digital components that can
include other or additional types of content besides images. For
example, the content items can include text, video, or audio
content. The images data can include image features for of the
respective images. The plurality of images can be digital
components that the data processing system 102 can select from to
provide to the first computing device in response to receiving the
request.
[0158] The method 900 can include extracting an image feature from
the first image (ACT 906). The recognition engine of the data
processing system 102 can apply image feature detection to the
first image to extract the image feature. The data processing
system 102 can also use the recognition engine to apply the image
feature detection to each of the plurality of images. The
recognition engine can extract one or more image features from each
of the images. The image features can include edges, corner
features, interest points, blobs or regions of interest, or ridge
features. The image features can be an identification of the
subject matter contained in the images. For example, for an image
of a shirt, the recognition engine can determine the image includes
a shirt. The image features can also include identification of
colors in the images. The recognition engine can use machine
learning or computer vision to identify the images features of each
of the images.
[0159] The method 900 can include selecting candidate images (ACT
908). The method 900 can include selecting the candidate images by
determining matches between the image feature of the first image
and the image features from each of the plurality of images. When
the recognition engine identifies a plurality of image features for
each of the images, the selection of the candidate images can be
based on matching a predetermined number of the image features
between the first image's image features and the image feature of
the plurality of images. In one example, the image feature of the
first image can be the identification that the first image
represents or otherwise includes a purse. The recognition engine
can select candidate images that also represent or otherwise
include a purse. In some implementations, meta data, such as
keywords associated with the plurality of images can also be used
select the candidate images. For example, the data processing
system 102 can select each of the plurality of images as candidate
images that are tagged with the keyword "purse."
[0160] The method 900 can include selecting a second image from the
candidate images (ACT 910). The second image can be selected based
on the request from the computing device. The second image can also
be selected from the candidate images based on the trigger keyword
that was identified by the NLP component 171. In some
implementations, the data processing system 102 can select a
template based on the trigger keyword. The data processing system
102 can generate an action data structure. The data processing
system 102 can populate fields in the template with the first or
second images. The data processing system 102 can also request a
value from a sensor associated with the computing device. The value
can be used to select the second image. The value can be populated
into an action data structure template. For example, the sensor can
be a GPS sensor and the value can be a location. The action data
structure can be generated by a direct action application
programming interface.
[0161] The method 900 can include transmitting the second image
(ACT 912). The second image can be transmitted to a second
computing device. The second computing device can be a computing
device that is associated with the first computing device. For
example, the first and the second computing device can be linked
through a user logging into a common account on each of the
computing devices. The second image can be transmitted to the
computing device by the data processing system 102 or by a service
provider computing device.
[0162] In some implementations, the method 900 can include
transmitting, by the direct action application programming
interface, the action data structure to a service provider
computing device to cause the service provider computing device to
invoke a conversational application programming interface. The
service provider computing device can establish a communication
session between the service provider computing device and the first
computing device. Through the communication session, the service
provider computing device can request information from the
computing device. The data processing system 102 can receive an
indication that the service provider computing device established
the communication session with the first computing device.
[0163] Although an example computing system has been described, the
subject matter including the operations described in this
specification can be implemented in other types of digital
electronic circuitry, or in computer software, firmware, or
hardware, including the structures disclosed in this specification
and their structural equivalents, or in combinations of one or more
of them.
[0164] For situations in which the systems discussed herein collect
personal information about users, or may make use of personal
information, the users may be provided with an opportunity to
control whether programs or features that may collect personal
information (e.g., information about a user's social network,
social actions or activities, a user's preferences, or a user's
location), or to control whether or how to receive content from a
content server or other data processing system 102 that may be more
relevant to the user. In addition, certain data may be anonymized
in one or more ways before it is stored or used, so that personally
identifiable information is removed when generating parameters. For
example, a user's identity may be anonymized so that no personally
identifiable information can be determined for the user, or a
user's geographic location may be generalized where location
information is obtained (such as to a city, postal code, or state
level), so that a particular location of a user cannot be
determined. Thus, the user may have control over how information is
collected about him or her and used by the content server.
[0165] The subject matter and the operations described in this
specification can be implemented in digital electronic circuitry,
or in computer software, firmware, or hardware, including the
structures disclosed in this specification and their structural
equivalents, or in combinations of one or more of them. The subject
matter described in this specification can be implemented as one or
more computer programs, e.g., one or more circuits of computer
program instructions, encoded on one or more computer storage media
for execution by, or to control the operation of, data processing
apparatuses. Alternatively, or in addition, the program
instructions can be encoded on an artificially generated propagated
signal, e.g., a machine-generated electrical, optical, or
electromagnetic signal that is generated to encode information for
transmission to suitable receiver apparatus for execution by a data
processing apparatus. A computer storage medium can be, or be
included in, a computer-readable storage device, a
computer-readable storage substrate, a random or serial access
memory array or device, or a combination of one or more of them.
While a computer storage medium is not a propagated signal, a
computer storage medium can be a source or destination of computer
program instructions encoded in an artificially generated
propagated signal. The computer storage medium can also be, or be
included in, one or more separate components or media (e.g.,
multiple CDs, disks, or other storage devices). The operations
described in this specification can be implemented as operations
performed by a data processing apparatus on data stored on one or
more computer-readable storage devices or received from other
sources.
[0166] The terms "data processing system" "computing device"
"component" or "data processing apparatus" encompass various
apparatuses, devices, and machines for processing data, including
by way of example a programmable processor, a computer, a system on
a chip, or multiple ones, or combinations of the foregoing. The
apparatus can include special purpose logic circuitry, e.g., an
FPGA (field programmable gate array) or an ASIC (application
specific integrated circuit). The apparatus can also include, in
addition to hardware, code that creates an execution environment
for the computer program in question, e.g., code that constitutes
processor firmware, a protocol stack, a database management system,
an operating system, a cross-platform runtime environment, a
virtual machine, or a combination of one or more of them. The
apparatus and execution environment can realize various different
computing model infrastructures, such as web services, distributed
computing and grid computing infrastructures. For example, the
direct action API 116, content selector component 118, or NLP
component 171 and data processing system 102 components can include
or share one or more data processing apparatuses, systems,
computing devices, or processors.
[0167] A computer program (also known as a program, software,
software application, app, script, or code) can be written in any
form of programming language, including compiled or interpreted
languages, declarative or procedural languages, and can be deployed
in any form, including as a stand-alone program or as a module,
component, subroutine, object, or other unit suitable for use in a
computing environment. A computer program can correspond to a file
in a file system. A computer program can be stored in a portion of
a file that holds other programs or data (e.g., one or more scripts
stored in a markup language document), in a single file dedicated
to the program in question, or in multiple coordinated files (e.g.,
files that store one or more modules, sub programs, or portions of
code). A computer program can be deployed to be executed on one
computer or on multiple computers that are located at one site or
distributed across multiple sites and interconnected by a
communication network.
[0168] The processes and logic flows described in this
specification can be performed by one or more programmable
processors executing one or more computer programs (e.g.,
components of the data processing system 102) to perform actions by
operating on input data and generating output. The processes and
logic flows can also be performed by, and apparatuses can also be
implemented as, special purpose logic circuitry, e.g., an FPGA
(field programmable gate array) or an ASIC (application specific
integrated circuit). Devices suitable for storing computer program
instructions and data include all forms of non-volatile memory,
media and memory devices, including by way of example semiconductor
memory devices, e.g., EPROM, EEPROM, and flash memory devices;
magnetic disks, e.g., internal hard disks or removable disks;
magneto optical disks; and CD ROM and DVD-ROM disks. The processor
and the memory can be supplemented by, or incorporated in, special
purpose logic circuitry.
[0169] The subject matter described herein can be implemented in a
computing system that includes a back end component, e.g., as a
data server, or that includes a middleware component, e.g., an
application server, or that includes a front end component, e.g., a
client computer having a graphical user interface or a web browser
through which a user can interact with an implementation of the
subject matter described in this specification, or a combination of
one or more such back end, middleware, or front end components. The
components of the system can be interconnected by any form or
medium of digital data communication, e.g., a communication
network. Examples of communication networks include a local area
network ("LAN") and a wide area network ("WAN"), an inter-network
(e.g., the Internet), and peer-to-peer networks (e.g., ad hoc
peer-to-peer networks).
[0170] The computing system such as system 100 or system 500 can
include clients and servers. A client and server are generally
remote from each other and typically interact through a
communication network (e.g., the network 165). The relationship of
client and server arises by virtue of computer programs running on
the respective computers and having a client-server relationship to
each other. In some implementations, a server transmits data (e.g.,
data packets representing a content item) to a client device (e.g.,
for purposes of displaying data to and receiving user input from a
user interacting with the client device). Data generated at the
client device (e.g., a result of the user interaction) can be
received from the client device at the server (e.g., received by
the data processing system 102 from the computing device 206 or the
content provider computing device 222 or the service provider
computing device 210).
[0171] While operations are depicted in the drawings in a
particular order, such operations are not required to be performed
in the particular order shown or in sequential order, and all
illustrated operations are not required to be performed. Actions
described herein can be performed in a different order.
[0172] The separation of various system components does not require
separation in all implementations, and the described program
components can be included in a single hardware or software
product. For example, the NLP component 171 or the content selector
component 118, can be a single component, app, or program, or a
logic device having one or more processing circuits, or part of one
or more servers of the data processing system 102.
[0173] Having now described some illustrative implementations, it
is apparent that the foregoing is illustrative and not limiting,
having been presented by way of example. In particular, although
many of the examples presented herein involve specific combinations
of method acts or system elements, those acts and those elements
may be combined in other ways to accomplish the same objectives.
Acts, elements and features discussed in connection with one
implementation are not intended to be excluded from a similar role
in other implementations or implementations.
[0174] The phraseology and terminology used herein is for the
purpose of description and should not be regarded as limiting. The
use of "including" "comprising" "having" "containing" "involving"
"characterized by" "characterized in that" and variations thereof
herein, is meant to encompass the items listed thereafter,
equivalents thereof, and additional items, as well as alternate
implementations consisting of the items listed thereafter
exclusively. In one implementation, the systems and methods
described herein consist of one, each combination of more than one,
or all of the described elements, acts, or components.
[0175] Any references to implementations or elements or acts of the
systems and methods herein referred to in the singular may also
embrace implementations including a plurality of these elements,
and any references in plural to any implementation or element or
act herein may also embrace implementations including only a single
element. References in the singular or plural form are not intended
to limit the presently disclosed systems or methods, their
components, acts, or elements to single or plural configurations.
References to any act or element being based on any information,
act or element may include implementations where the act or element
is based at least in part on any information, act, or element.
[0176] Any implementation disclosed herein may be combined with any
other implementation or embodiment, and references to "an
implementation," "some implementations," "one implementation" or
the like are not necessarily mutually exclusive and are intended to
indicate that a particular feature, structure, or characteristic
described in connection with the implementation may be included in
at least one implementation or embodiment. Such terms as used
herein are not necessarily all referring to the same
implementation. Any implementation may be combined with any other
implementation, inclusively or exclusively, in any manner
consistent with the aspects and implementations disclosed
herein.
[0177] References to "or" may be construed as inclusive so that any
terms described using "or" may indicate any of a single, more than
one, and all of the described terms. For example, a reference to
"at least one of `A` and `B`" can include only `A`, only `B`, as
well as both `A` and `B`. Such references used in conjunction with
"comprising" or other open terminology can include additional
items.
[0178] Where technical features in the drawings, detailed
description or any claim are followed by reference signs, the
reference signs have been included to increase the intelligibility
of the drawings, detailed description, and claims. Accordingly,
neither the reference signs nor their absence have any limiting
effect on the scope of any claim elements.
[0179] The systems and methods described herein may be embodied in
other specific forms without departing from the characteristics
thereof. For example, the data processing system 102 can select a
content item or digital component for a subsequent action (e.g.,
for the third action) based in part on data from a prior action in
the sequence of actions of the thread, such as data from the second
action indicating that the second action is complete or about to
begin. The foregoing implementations are illustrative rather than
limiting of the described systems and methods. Scope of the systems
and methods described herein is thus indicated by the appended
claims, rather than the foregoing description, and changes that
come within the meaning and range of equivalency of the claims are
embraced therein.
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