U.S. patent application number 15/290999 was filed with the patent office on 2017-12-28 for systems and methods for identifying matching content.
The applicant listed for this patent is Facebook, Inc.. Invention is credited to Sergiy Bilobrov.
Application Number | 20170372142 15/290999 |
Document ID | / |
Family ID | 60675542 |
Filed Date | 2017-12-28 |
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United States Patent
Application |
20170372142 |
Kind Code |
A1 |
Bilobrov; Sergiy |
December 28, 2017 |
SYSTEMS AND METHODS FOR IDENTIFYING MATCHING CONTENT
Abstract
Systems, methods, and non-transitory computer-readable media can
obtain a test content item having a plurality of video frames. At
least one video fingerprint is determined based on a set of video
frames corresponding to the test content item. At least one
reference content item is determined using at least a portion of
the video fingerprint. At least one portion of the test content
item that matches at least one portion of the reference content
item is determined based at least in part on the video fingerprint
of the test content item and one or more video fingerprints of the
reference content item.
Inventors: |
Bilobrov; Sergiy; (Santa
Clara, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Facebook, Inc. |
Menlo Park |
CA |
US |
|
|
Family ID: |
60675542 |
Appl. No.: |
15/290999 |
Filed: |
October 11, 2016 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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62355043 |
Jun 27, 2016 |
|
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04N 21/233 20130101;
G06K 9/4652 20130101; G06K 9/00744 20130101; G06K 9/4604 20130101;
G06F 16/71 20190101; G06K 9/4633 20130101; G06F 16/2237 20190101;
G06K 9/00751 20130101; G06F 16/2255 20190101; G06F 16/783 20190101;
H04N 21/8358 20130101; G06F 16/2455 20190101; G06K 9/4671 20130101;
G06F 16/2228 20190101; H04N 21/2187 20130101; H04N 21/23418
20130101; G06F 16/785 20190101 |
International
Class: |
G06K 9/00 20060101
G06K009/00; H04N 21/233 20110101 H04N021/233; G06K 9/46 20060101
G06K009/46; H04N 21/2187 20110101 H04N021/2187; H04N 21/8358
20110101 H04N021/8358; H04N 21/234 20110101 H04N021/234 |
Claims
1. A computer-implemented method comprising: evaluating, by a
computing system, at least one portion of a test content item with
at least one portion of a reference content item using one or more
first fingerprints of the test content item and one or more first
fingerprints of the reference content item, wherein the first
fingerprints correspond to a first type of media; determining, by
the computing system, that at least one verification criteria is
satisfied; and evaluating, by the computing system, the portion of
the test content with the portion of the reference content using
one or more second fingerprints of the test content item and one or
more second fingerprints of the reference content item, wherein the
second fingerprints correspond to a second type of media that is
different from the first type of media.
2. The computer-implemented method of claim 1, wherein evaluating
the portion of the test content with the portion of the reference
content further comprises: obtaining, by the computing system, the
one or more second fingerprints that correspond to the portion of
the test content item; obtaining, by the computing system, the one
or more second fingerprints that correspond to the portion of the
reference content item; and determining, by the computing system,
that the portion of the test content item matches the portion of
the reference content item using the second fingerprints of the
test content item and the second fingerprints of the reference
content item.
3. The computer-implemented method of claim 1, wherein determining
that at least one verification criteria is satisfied further
comprises: determining, by the computing system, that the portion
of the test content item does not match the portion of the
reference content item using the first fingerprints of the test
content item and the first fingerprints of the reference content
item.
4. The computer-implemented method of claim 1, wherein determining
that at least one verification criteria is satisfied further
comprises: determining, by the computing system, that the portion
of the test content item matches the portion of the reference
content item using the first fingerprints of the test content item
and the first fingerprints of the reference content item.
5. The computer-implemented method of claim 1, wherein determining
that at least one verification criteria is satisfied further
comprises: determining, by the computing system, that no matches
were determined between the test content item and the reference
content item for a threshold period of time.
6. The computer-implemented method of claim 1, wherein determining
that at least one verification criteria is satisfied further
comprises: determining, by the computing system, that no matches
were determined between the test content item and the reference
content item for a threshold number of frames.
7. The computer-implemented method of claim 1, wherein the first
fingerprints and the second fingerprints correspond to one of:
audio fingerprints, video fingerprints, or thumbnail
fingerprints.
8. The computer-implemented method of claim 1, wherein the first
fingerprints correspond to audio fingerprints, and wherein the
second fingerprints correspond to video fingerprints.
9. The computer-implemented method of claim 1, wherein the first
fingerprints correspond to thumbnail fingerprints, and wherein the
second fingerprints correspond to video fingerprints.
10. The computer-implemented method of claim 1, the method further
comprising: evaluating, by the computing system, the portion of the
test content with the portion of the reference content using one or
more third fingerprints of the test content item and one or more
third fingerprints of the reference content item, wherein the third
fingerprints correspond to a third type of media that is different
from the first type of media and the second type of media.
11. A system comprising: at least one processor; and a memory
storing instructions that, when executed by the at least one
processor, cause the system to perform: evaluating at least one
portion of a test content item with at least one portion of a
reference content item using one or more first fingerprints of the
test content item and one or more first fingerprints of the
reference content item, wherein the first fingerprints correspond
to a first type of media; determining that at least one
verification criteria is satisfied; and evaluating the portion of
the test content with the portion of the reference content using
one or more second fingerprints of the test content item and one or
more second fingerprints of the reference content item, wherein the
second fingerprints correspond to a second type of media that is
different from the first type of media.
12. The system of claim 11, wherein evaluating the portion of the
test content with the portion of the reference content further
causes the system to perform: obtaining the one or more second
fingerprints that correspond to the portion of the test content
item; obtaining the one or more second fingerprints that correspond
to the portion of the reference content item; and determining that
the portion of the test content item matches the portion of the
reference content item using the second fingerprints of the test
content item and the second fingerprints of the reference content
item.
13. The system of claim 12, wherein determining that at least one
verification criteria is satisfied further causes the system to
perform: determining that the portion of the test content item does
not match the portion of the reference content item using the first
fingerprints of the test content item and the first fingerprints of
the reference content item.
14. The system of claim 11, wherein the system further causes the
system to perform: determining that the broadcaster of the second
live content stream is continuing to provide the second live
content stream despite having received the at least one
notification; and determining that the portion of the test content
item matches the portion of the reference content item using the
first fingerprints of the test content item and the first
fingerprints of the reference content item.
15. The system of claim 14, wherein providing at least one
notification to the publisher of the first live content stream
further causes the system to perform: determining that no matches
were determined between the test content item and the reference
content item for a threshold period of time.
16. A non-transitory computer-readable storage medium including
instructions that, when executed by at least one processor of a
computing system, cause the computing system to perform a method
comprising: evaluating at least one portion of a test content item
with at least one portion of a reference content item using one or
more first fingerprints of the test content item and one or more
first fingerprints of the reference content item, wherein the first
fingerprints correspond to a first type of media; determining that
at least one verification criteria is satisfied; and evaluating the
portion of the test content with the portion of the reference
content using one or more second fingerprints of the test content
item and one or more second fingerprints of the reference content
item, wherein the second fingerprints correspond to a second type
of media that is different from the first type of media.
17. The non-transitory computer-readable storage medium of claim
16, wherein evaluating the portion of the test content with the
portion of the reference content further causes the computing
system to perform: obtaining the one or more second fingerprints
that correspond to the portion of the test content item; obtaining
the one or more second fingerprints that correspond to the portion
of the reference content item; and determining that the portion of
the test content item matches the portion of the reference content
item using the second fingerprints of the test content item and the
second fingerprints of the reference content item.
18. The non-transitory computer-readable storage medium of claim
17, wherein determining that at least one verification criteria is
satisfied further performs: determining that the portion of the
test content item does not match the portion of the reference
content item using the first fingerprints of the test content item
and the first fingerprints of the reference content item.
19. The non-transitory computer-readable storage medium of claim
16, wherein determining that at least one verification criteria is
satisfied further performs: determining that the portion of the
test content item matches the portion of the reference content item
using the first fingerprints of the test content item and the first
fingerprints of the reference content item.
20. The non-transitory computer-readable storage medium of claim
19, wherein determining that at least one verification criteria is
satisfied further causes the computing system to perform:
determining that no matches were determined between the test
content item and the reference content item for a threshold period
of time.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority to U.S. Provisional Patent
Application No. 62/355,043, filed on Jun. 27, 2016 and entitled
"SYSTEMS AND METHODS FOR IDENTIFYING MATCHING CONTENT", which is
incorporated in its entirety herein by reference.
FIELD OF THE INVENTION
[0002] The present technology relates to the field of content
matching. More particularly, the present technology relates to
techniques for identifying matching content items.
BACKGROUND
[0003] Today, people often utilize computing devices (or systems)
for a wide variety of purposes. Users can use their computing
devices to, for example, interact with one another, access content,
share content, and create content. In some cases, content items can
include postings from members of a social network. The postings may
include text and media content items, such as images, videos, and
audio. The postings may be published to the social network for
consumption by others.
SUMMARY
[0004] Various embodiments of the present disclosure can include
systems, methods, and non-transitory computer readable media
configured to obtain a test content item having a plurality of
video frames, generate at least one video fingerprint based on a
set of video frames corresponding to the test content item,
determine at least one reference content item using at least a
portion of the video fingerprint, and determine at least one
portion of the test content item that matches at least one portion
of the reference content item based at least in part on the video
fingerprint of the test content item and one or more video
fingerprints of the reference content item.
[0005] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to generate a respective
feature vector for each video frame in the set of video frames,
wherein a feature vector includes a set of feature values that
describe a video frame, convert the feature vectors for the set of
video frames to a frequency domain, and generate a respective set
of bits for each video frame by quantizing a set of frequency
components that correspond to one or more of the video frames.
[0006] In an embodiment, the feature values included in a feature
vector of a video frame correspond to at least a measured
brightness for the video frame, a measured coloration for the video
frame, or measured changes between one or more groups of pixels in
the video frame.
[0007] In an embodiment, a feature vector for a video frame is
converted to a frequency domain by applying a Fast Fourier
Transform (FFT), a Discrete Cosine Transform (DCT), or both.
[0008] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to interpolate the video
frames in the frequency domain, wherein the interpolation causes
the video fingerprint to correspond to a pre-defined frame
rate.
[0009] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to obtain a set of bits
corresponding to a first frame in the set of frames from which the
video fingerprint was generated, identify at least one candidate
frame based at least in part on a first portion of the set of bits,
and determine the reference content item based on the candidate
frame.
[0010] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to hash the first portion of
the set of bits to a bin in an inverted index, wherein the bin
references information describing the at least one candidate
frame.
[0011] In an embodiment, the information describing the candidate
frame identifies the reference content item and an offset that
identifies a position of the candidate frame in the reference
content item.
[0012] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to obtain a set of bits
corresponding to at least one first frame in the set of frames from
which the video fingerprint was generated, identify at least one
candidate frame based at least in part on a first portion of the
set of bits, and determine that a Hamming distance between the set
of bits corresponding to the first frame and a set of bits
corresponding to the candidate frame satisfies a threshold
value.
[0013] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to obtain a set of bits
corresponding to at least one second frame in the set of frames
from which the video fingerprint was generated, determine a set of
bits corresponding to a new frame in the reference content item,
and determine that a Hamming distance between the set of bits
corresponding to the second frame and the set of bits corresponding
to the new frame satisfies a threshold value.
[0014] Various embodiments of the present disclosure can include
systems, methods, and non-transitory computer readable media
configured to evaluate at least one portion of a test content item
with at least one portion of a reference content item using one or
more first fingerprints of the test content item and one or more
first fingerprints of the reference content item, wherein the first
fingerprints correspond to a first type of media, determine that at
least one verification criteria is satisfied, and evaluate the
portion of the test content with the portion of the reference
content using one or more second fingerprints of the test content
item and one or more second fingerprints of the reference content
item, wherein the second fingerprints correspond to a second type
of media that is different from the first type of media.
[0015] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to obtain the one or more
second fingerprints that correspond to the portion of the test
content item, obtain the one or more second fingerprints that
correspond to the portion of the reference content item, and
determine that the portion of the test content item matches the
portion of the reference content item using the second fingerprints
of the test content item and the second fingerprints of the
reference content item.
[0016] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to determine that the
portion of the test content item does not match the portion of the
reference content item using the first fingerprints of the test
content item and the first fingerprints of the reference content
item.
[0017] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to determine that the
portion of the test content item matches the portion of the
reference content item using the first fingerprints of the test
content item and the first fingerprints of the reference content
item.
[0018] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to determine that no matches
were determined between the test content item and the reference
content item for a threshold period of time.
[0019] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to determine that no matches
were determined between the test content item and the reference
content item for a threshold number of frames.
[0020] In an embodiment, the first fingerprints and the second
fingerprints correspond to one of: audio fingerprints, video
fingerprints, or thumbnail fingerprints.
[0021] In an embodiment, the first fingerprints correspond to audio
fingerprints, and wherein the second fingerprints correspond to
video fingerprints.
[0022] In an embodiment, the first fingerprints correspond to
thumbnail fingerprints, and wherein the second fingerprints
correspond to video fingerprints.
[0023] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to evaluate the portion of
the test content with the portion of the reference content using
one or more third fingerprints of the test content item and one or
more third fingerprints of the reference content item, wherein the
third fingerprints correspond to a third type of media that is
different from the first type of media and the second type of
media.
[0024] Various embodiments of the present disclosure can include
systems, methods, and non-transitory computer readable media
configured to generate at least one fingerprint based on a set of
frames corresponding to a test content item, generate a set of
distorted fingerprints using at least a portion of the fingerprint,
and determine one or more reference content items using the set of
distorted fingerprints, wherein the test content item is evaluated
against at least one reference content item to identify matching
content.
[0025] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to obtain a set of bits
corresponding to a first frame in the set of frames from which the
fingerprint was generated and generate a set of binary string
permutations for at least a portion of the set of bits.
[0026] In an embodiment, one or more bits are permuted in each
binary string.
[0027] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to generate a first set of
binary string permutations for the portion of the set of bits,
wherein one bit is permuted in each binary string, determine that
no reference content items were identified using the first set of
binary string permutations, and generate a second set of binary
string permutations for the portion of the set of bits, wherein
multiple bits are permuted in each binary string.
[0028] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to obtain a set of bits
corresponding to a first distorted fingerprint, identify at least
one candidate frame based at least in part on a portion of the set
of bits, and determine at least one reference content item based on
the candidate frame.
[0029] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to hash the portion of the
set of bits to a bin in an inverted index, wherein the bin
references information describing the at least one candidate frame
and the reference content item.
[0030] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to determine that
identifying reference content items using the set of distorted
fingerprints will not cause a central processing unit (CPU) load of
the computing system to exceed a threshold load.
[0031] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to determine that no
reference content items were identified using the at least one
fingerprint.
[0032] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to determine at least one
reference content item using the at least one fingerprint and
determine that no matches between the test content item and the
reference content item were identified.
[0033] In an embodiment, the systems, methods, and non-transitory
computer readable media are configured to determine at least one
reference content item using the at least one fingerprint and
determine that a match between the test content item and the
reference content item is within a threshold match distance.
[0034] It should be appreciated that many other features,
applications, embodiments, and/or variations of the disclosed
technology will be apparent from the accompanying drawings and from
the following detailed description. Additional and/or alternative
implementations of the structures, systems, non-transitory computer
readable media, and methods described herein can be employed
without departing from the principles of the disclosed
technology.
BRIEF DESCRIPTION OF THE DRAWINGS
[0035] FIG. 1 illustrates an example system including an example
content provider module configured to provide access to various
content items, according to an embodiment of the present
disclosure.
[0036] FIG. 2 illustrates an example of a content matching module,
according to an embodiment of the present disclosure.
[0037] FIG. 3 illustrates an example of a fingerprinting module,
according to an embodiment of the present disclosure.
[0038] FIG. 4 illustrates an example of a storage module, according
to an embodiment of the present disclosure.
[0039] FIG. 5 illustrates an example of a matching module,
according to an embodiment of the present disclosure.
[0040] FIG. 6 illustrates an example approach for extracting
feature values from a frame, according to an embodiment of the
present disclosure.
[0041] FIG. 7 illustrates an example inverted index for storing and
retrieval fingerprint data, according to an embodiment of the
present disclosure.
[0042] FIGS. 8A-B illustrate an example approach for identifying
matching content between content items, according to an embodiment
of the present disclosure.
[0043] FIGS. 9A-C illustrate an example approach for processing a
live content stream, according to an embodiment of the present
disclosure.
[0044] FIG. 10 illustrates an example process for fingerprinting
content, according to various embodiments of the present
disclosure.
[0045] FIG. 11 illustrates an example process for matching content
using different types of fingerprints, according to various
embodiments of the present disclosure.
[0046] FIG. 12 illustrates an example process for matching content
using distorted fingerprints, according to various embodiments of
the present disclosure.
[0047] FIG. 13 illustrates a network diagram of an example system
including an example social networking system that can be utilized
in various scenarios, according to an embodiment of the present
disclosure.
[0048] FIG. 14 illustrates an example of a computer system or
computing device that can be utilized in various scenarios,
according to an embodiment of the present disclosure.
[0049] The figures depict various embodiments of the disclosed
technology for purposes of illustration only, wherein the figures
use like reference numerals to identify like elements. One skilled
in the art will readily recognize from the following discussion
that alternative embodiments of the structures and methods
illustrated in the figures can be employed without departing from
the principles of the disclosed technology described herein.
DETAILED DESCRIPTION
Approaches for Identifying Matching Content
[0050] Today, people often utilize computing devices (or systems)
for a wide variety of purposes. Users can use their computing
devices to, for example, interact with one another, access content,
share content, and create content. In some cases, content items can
include postings from members of a social network. The postings may
include text and media content items, such as images, videos, and
audio. The postings may be published to the social network for
consumption by others.
[0051] Under conventional approaches, content may be broadcast
through a content provider. For example, such content providers may
broadcast content through various broadcast mediums (e.g.,
television, satellite, Internet, etc.). In one example, a broadcast
can include content that is being captured and streamed live by a
publisher. For example, a publisher can provide content (e.g., live
concert, TV show premiere, etc.) to be broadcasted as part of a
live content stream. Such events can be captured using, for
example, video capture devices (e.g., video cameras) and/or audio
capture devices (e.g., microphones). This captured content can then
be encoded and distributed to user devices over a network (e.g.,
the Internet) in real-time by a content provider (e.g., a social
networking system). In some instances, an unauthorized entity may
capture a copy of the publisher's live content stream and stream
the copied content through the content provider as part of a
separate live content stream. For example, this entity may record a
video of the publisher's live content stream as the content is
being presented on a television display. In another example, the
unauthorized entity may capture a stream of the event being
broadcasted through a different medium (e.g., satellite, etc.) and
publish the captured stream through the content provider.
[0052] Under conventional approaches, it can be difficult to detect
such unauthorized live content streams and this difficulty can be
especially problematic when the live content streams contain
copyrighted content. For example, under conventional approaches, a
content provider would typically check whether a content item is
infringing a copyrighted content item after the content item has
been uploaded to the content provider in its entirety. The content
provider would then analyze the uploaded content item against the
copyrighted content item to identify whether any portions match.
While such approaches may be adequate for detecting copyright
infringement in content items that are served on-demand, they are
generally inadequate for detecting copyright infringement in
content items that are being streamed live. Accordingly, such
conventional approaches may not be effective in addressing these
and other problems arising in computer technology.
[0053] An improved approach rooted in computer technology overcomes
the foregoing and other disadvantages associated with conventional
approaches specifically arising in the realm of computer
technology. In various embodiments, a publisher can provide content
to be streamed, or broadcasted, through a social networking system
as part of a live content stream. The publisher can indicate that
the live content stream is copyrighted and, based on this
indication, the social networking system can generate fingerprints
of the content as the content is streamed live. These fingerprints
can be stored in a reference database, for example, and used for
identifying duplicate content in other live content streams and/or
on-demand content items. For example, as the publisher's content is
being streamed live, the social networking system can determine
whether any other live content streams and/or on-demand content
items match the publisher's copyrighted live content stream either
in whole or in part. Any portion of content items that match the
publisher's live content stream may be violations of copyrights or
other legal rights. In such instances, the unauthorized
broadcasters and/or the publisher of the live content stream (e.g.,
copyright holder) can be notified about the possible copyright
violations and appropriate action can be taken. In some
embodiments, the infringing live content streams and/or on-demand
content item posted by the unauthorized broadcaster is
automatically made inaccessible through the social networking
system.
[0054] FIG. 1 illustrates an example system 100 including an
example content provider module 102 configured to provide access to
various content items, according to an embodiment of the present
disclosure. As shown in the example of FIG. 1, the content provider
module 102 can include a content upload module 104. a live stream
module 106, a content module 108, and a content matching module
110. In some instances, the example system 100 can include at least
one data store 112. The components (e.g., modules, elements, etc.)
shown in this figure and all figures herein are exemplary only, and
other implementations may include additional, fewer, integrated, or
different components. Some components may not be shown so as not to
obscure relevant details.
[0055] In some embodiments, the content provider module 102 can be
implemented, in part or in whole, as software, hardware, or any
combination thereof. In general, a module as discussed herein can
be associated with software, hardware, or any combination thereof.
In some implementations, one or more functions, tasks, and/or
operations of modules can be carried out or performed by software
routines, software processes, hardware, and/or any combination
thereof. In some cases, the content provider module 102 can be
implemented, in part or in whole, as software running on one or
more computing devices or systems, such as on a user or client
computing device. In one example, the content provider module 102
or at least a portion thereof can be implemented as or within an
application (e.g., app), a program, or an applet, etc., running on
a user computing device or a client computing system, such as the
user device 1310 of FIG. 13. In another example, the content
provider module 102 or at least a portion thereof can be
implemented using one or more computing devices or systems that
include one or more servers, such as network servers or cloud
servers. In some instances, the content provider module 102 can, in
part or in whole, be implemented within or configured to operate in
conjunction with a social networking system (or service), such as
the social networking system 1330 of FIG. 13.
[0056] The content provider module 102 can be configured to
communicate and/or operate with the at least one data store 112, as
shown in the example system 100. The at least one data store 112
can be configured to store and maintain various types of data. For
example, the data store 112 can store information describing
various content that is being streamed live through the social
networking system or content items that have been posted by users
of the social networking system. Such information can include, for
example, fingerprints (e.g., bit sequences) that were generated for
live content streams and for on-demand content items. In some
implementations, the at least one data store 112 can store
information associated with the social networking system (e.g., the
social networking system 1330 of FIG. 13). The information
associated with the social networking system can include data about
users, social connections, social interactions, locations,
geo-fenced areas, maps, places, events, pages, groups, posts,
communications, content, feeds, account settings, privacy settings,
a social graph, and various other types of data. In some
implementations, the at least one data store 112 can store
information associated with users, such as user identifiers, user
information, profile information, user specified settings, content
produced or posted by users, and various other types of user
data.
[0057] The content provider module 102 can be configured to provide
users with access to content items that are posted through a social
networking system. For example, a user can interact with an
interface that is provided by a software application (e.g., a
social networking application) running on a computing device of the
user. This interface can include an option for posting, or
uploading, content items to the social networking system. When
posting a content item, the content upload module 104 can be
utilized to communicate data describing the content item from the
computing device to the social networking system. Such content
items may include text, images, audio, and videos, for example. The
social networking system can then provide the content item through
the social networking system including, for example, in one or more
news feeds. In some embodiments, the interface can also include an
option for live streaming content items through the social
networking system. When initiating a live content stream, the live
stream module 106 can be utilized to communicate data describing
the content to be streamed live from the computing device to the
social networking system. The live stream module 106 can utilize
any generally known techniques that allow for live streaming of
content including, for example, the Real Time Messaging Protocol
(RTMP).
[0058] The interface provided by the software application can also
be used to access posted content items, for example, using the
content module 108. For example, the content module 108 can include
content items in a user's news feed. Such content items may include
on-demand content items (e.g., video on-demand or "VOD") as well as
content that is being streamed live. In this example, the user can
access content items while browsing the news feed. In another
example, the user can access content items by searching, through
the interface, for a content item, for the user that posted a
content item, and/or using search terms that correspond to a
content item. In one example, the user may select an option to view
a live content stream and, in response, the social networking
system can send data corresponding to the live content stream to a
computing device of the user. In this example, the social
networking system can continue sending data corresponding to the
live content stream until, for example, the publisher of the live
content stream discontinues streaming or if the user selects an
option to discontinue the live content stream. The content matching
module 110 can be configured to identify matches (e.g., copyright
infringement) between content items that are being streamed live or
are available on-demand through the social networking system. More
details regarding the content matching module 110 will be provided
below with reference to FIG. 2.
[0059] FIG. 2 illustrates an example of a content matching module
202, according to an embodiment of the present disclosure. In some
embodiments, the content matching module 110 of FIG. 1 can be
implemented as the content matching module 202. As shown in FIG. 2,
the content matching module 202 can include a fingerprinting module
204, a storage module 206, a matching module 208, and a
notification module 210.
[0060] In various embodiments, the fingerprinting module 204 is
configured to determine, or obtain, respective fingerprints for
content items. For example, a set of fingerprints for a live
content stream may be determined as the stream is received by the
social networking system. In another example, a set of fingerprints
can be determined for a content item after the content item is
uploaded to the social networking system. In some embodiments, a
publisher that is live streaming or uploading a content item may
select an option to indicate that the content item is protected,
e.g., copyrighted. In such embodiments, the live content stream or
uploaded content item can be fingerprinted and stored, for example,
in a reference database (e.g., the data store 112 of FIG. 1), in
response to the option being selected. The fingerprints stored in
this reference database can be used to determine whether other
content items that are available through the social networking
system, either as live streams or videos on-demand, match (e.g.,
infringe) content that has been identified as being protected,
e.g., copyrighted.
[0061] In some embodiments, the fingerprinting module 204 can
obtain fingerprints for content items from one or more
fingerprinting services that are each configured to determine
fingerprints using one or more techniques. Such fingerprints may be
determined, for example, using video data corresponding to the
content item, audio data corresponding to the content item, or
both. More details regarding the fingerprinting module 204 will be
provided below with reference to FIG. 3.
[0062] The storage module 206 can be configured to manage the
storage of information related to various content items. In various
embodiments, the storage module 206 is configured to optimize the
storage of fingerprints that are obtained, or generated, for
content items. More details regarding the storage module 206 will
be provided below with reference to FIG. 4.
[0063] In various embodiments, the matching module 208 is
configured to determine a measure of relatedness between content
items. Such measurements can be used to determine whether a content
item (e.g., a live content stream and/or on-demand content item)
matches, in whole or in part, any portions of a live content
stream, any portions of content that were recently streamed live,
and/or any portions of videos that are available on-demand through
the social networking system. For example, the matching module 208
can determine that one or more portions (e.g., frames) of a
protected live content stream match one or more portions (e.g.,
frames) of a candidate live stream. In some embodiments, the
matching module 208 can be utilized to identify and segregate
content items that include any content that has been flagged as
including inappropriate or obscene content. More details regarding
the matching module 208 will be provided below with reference to
FIG. 5.
[0064] The notification module 210 can be configured to take
various actions in response to any protected content being copied
(e.g., copyright violations, potential or otherwise). For example,
upon determining a threshold content match between a first content
item (e.g., a protected live content stream) and a second content
item (e.g., a candidate live content stream), the notification
module 210 can notify the broadcaster of the candidate live content
stream of the copying (e.g., potential copyright infringement). In
some embodiments, the broadcaster has the option to end the
candidate live content stream or to continue the live content
stream. In such embodiments, by continuing the live content stream,
the broadcaster is asserting its rights to stream the candidate
live content stream. In some cases, if the broadcaster ends the
candidate live content stream, then no action is needed from the
publisher and, depending on the implementation, the publisher may
or may not be notified of the broadcaster's live content stream.
However, if the broadcaster decides to continue the candidate live
content stream, then the notification module 210 can provide the
publisher with information about the matching content. In some
embodiments, the publisher can access an interface provided by the
notification module 210 that identifies the respective portions of
the candidate live content stream at which matches were found. The
publisher can access the interface to playback the matching
portions of the content items. The publisher can also access the
interface to flag live content streams and/or uploaded content
items as a copy violations (e.g., copyright violations), to take no
action (e.g., due to fair use of the content item), or to grant
authorization for use of the protected (e.g., copyrighted)
portions, for example. In some embodiments, any live content
streams and/or uploaded content items that were flagged as
infringements of the publisher's protected content are made
inaccessible to users through the social networking system. In some
embodiments, the publisher can create match rules that specify
various criteria to be satisfied before the publisher is notified
of a match. For example, in some embodiments, the publisher can
specify a match type (e.g., audio, video, video only, audio only,
or both audio and video). In this example, the publisher is
notified of a match provided the match satisfies the match type. In
some embodiments, the publisher can specify a geographic region
(e.g., specific cities, states, regions, countries, worldwide,
etc.). In this example, the publisher is notified of a match
provided the matching content originated from, or was broadcasted
from, the specified geographic region. In some embodiments, the
publisher can specify one or more match conditions and actions to
be performed should those conditions be satisfied. One example
match condition involves setting a match time duration. In this
example, the publisher can be notified if the time length of
matching content satisfies (e.g., is greater than, equal to, or
less than) the match time duration. In some embodiments, the
publisher can specify a match length (e.g., number of frames) and
be notified if the matching content satisfies the specified match
length. In some embodiments, the publisher can specify one or more
approved, or whitelisted, users and/or pages that are permitted to
use the publisher's protected content. In such embodiments, the
publisher is notified if the matching content was posted by any
user or page that is not approved or whitelisted. In some
embodiments, the publisher can blacklist users and/or pages and be
notified if the matching content originates from the blacklisted
users and/or is broadcasted through blacklisted pages. In some
embodiments, the publisher can specify one or more actions to be
performed when match rules is satisfied. For example, the publisher
can specify that no action should be taken against a match that
satisfies a certain rule or rules. In another example, the
publisher can indicate that a notification, or report, should be
sent to the publisher when a match satisfies a certain rule or
rules. The match rules and conditions described above are provided
as examples and, in some embodiments, the publisher can create
match rules using other constraints. In general, any of the example
match rules and/or conditions described above can be combined with
other rules and/or conditions.
[0065] FIG. 3 illustrates an example of a fingerprinting module
302, according to an embodiment of the present disclosure. In some
embodiments, the fingerprinting module 204 of FIG. 2 can be
implemented as the fingerprinting module 302. As shown in FIG. 3,
the fingerprinting module 302 can include an audio fingerprinting
module 304, a video fingerprinting module 306, a thumbnail
fingerprinting module 308, and a distributed fingerprinting module
310.
[0066] The audio fingerprinting module 304 can be configured to
obtain, or generate, audio fingerprints for content items. Such
audio fingerprints can be generated using a variety of generally
known techniques. In some embodiments, the audio fingerprinting
module 304 obtains, or generates, audio fingerprints from an audio
signal that corresponds to a content item. The audio signal may be
composed of one or more discrete audio frames that each correspond
to a portion of the audio signal at some time. Each audio frame can
correspond to a portion of the audio signal over some length of
time (e.g., 32 milliseconds, 64 milliseconds, 128 milliseconds,
etc.). In some embodiments, each audio frame corresponds to a fixed
length of time. For example, each audio frame can represent some
portion of the audio signal and be 64 milliseconds in length. Some
examples of features that may be extracted from the audio signal
can include acoustic features in a frequency domain (e.g., spectral
features computed on the magnitude spectrum of the audio signal),
Mel-frequency cepstral coefficients (MFCC) of the audio signal,
spectral bandwidth and spectral flatness measure of the audio
signal, a spectral fluctuation, extreme value frequencies, and
silent frequencies of the audio signal. The audio features
extracted from the audio signal may also include features in a
temporal domain, such as the mean, standard deviation and the
covariance matrix of feature vectors over a texture window of the
audio signal. Other features may be extracted separately, or in
addition to, the examples described above including, for example,
volume changes of the audio signal over some period of time as well
as a compression format of the audio signal if the audio signal is
compressed.
[0067] The audio fingerprinting module 304 can generate an audio
fingerprint from one or more of the audio frames of the audio
signal. In some embodiments, an audio fingerprint corresponding to
some portion of the audio signal is generated based on various
acoustic and/or perceptual characteristics captured by the portion
of the audio signal. The audio fingerprint computed for a frame can
be represented as a set of bits (e.g., 32 bits, 64 bits, 128 bits,
etc.) that represent the waveform, or frame, to which the audio
fingerprint corresponds. In some embodiments, the audio
fingerprinting module 304 preprocesses the audio signal, transforms
the audio signal from one domain (e.g., time domain) to another
domain (e.g., frequency domain), filters the transformed audio
signal, and generates the audio fingerprint from the filtered audio
signal. In some embodiments, the audio fingerprint is generated
using a Discrete Cosine Transform (DCT). In some embodiments, a
match between a first audio fingerprint and a second audio
fingerprint may be determined when a Hamming distance between the
set of bits corresponding to the first audio fingerprint and the
set of bits corresponding to the second audio fingerprint satisfies
a threshold value. More details describing such audio fingerprint
generation and matching are described in U.S. patent application
Ser. Nos. 14/153,404 and 14/552,039, both of which are incorporated
by reference herein. Audio fingerprints that are generated for
content items can be stored and used for identifying matching
content. In some instances, a portion of a content item may include
silence, i.e., no perceptible audio. For example, a determination
may be made that a portion of a content item is audibly silent
based on an audio waveform corresponding to the content item. In
some embodiments, audio fingerprints generated for portions
containing silent content can be flagged, for example, by changing
the bit strings of those audio fingerprints to all zeros. In such
embodiments, portions of the content item that have been marked as
silent can be skipped when performing fingerprint matching.
[0068] In some embodiments, each audio fingerprint corresponds to a
pre-defined frame rate (e.g., 8 frames per second, 16 frames per
second, 32 frames per second, etc.). For example, at 16 frames per
second, an audio fingerprint of a content item can correspond to a
series of frames (e.g., 16 audio frames) and can represent one
second of audio in the content item. In this example, each of the
16 frames corresponding to the audio fingerprint may be represented
as a set of 64 bits or a 64 bit integer. In some embodiments, audio
fingerprints, video fingerprints, and thumbnail fingerprints are
generated by the fingerprinting module 302 at the same pre-defined
frame rate. More details describing the storage and retrieval of
audio fingerprints will be provided below with reference to FIG.
4.
[0069] The video fingerprinting module 306 can be configured to
obtain, or generate, video fingerprints for content items. In some
embodiments, when computing a video fingerprint, the video
fingerprinting module 306 converts data describing a set of video
frames (e.g., 8 frames, 16 frames, 32 frames, etc.) of the content
item from a time domain to a frequency domain. For example, the set
of frames may be a set of consecutive frames (e.g., Frame 1 to
Frame 8, Frame 1 to Frame 16, etc.) in the content item. In such
embodiments, the video fingerprinting module 306 determines
respective feature values for the set of frames to be used for
converting the frames into frequency domain. A feature value for a
frame can be determined based on one or more features corresponding
to the frame. In one example, a feature value for a frame can be
determined by calculating a brightness of the frame, for example,
by averaging the values of pixels in the frame. In another example,
a feature value for a frame can be determined based on coloration
components in the frame, for example, based on the RGB color model
and/or the YUV color space. Each feature value for the set of
frames can be included in an array or buffer. These feature values
can then be transformed into one or more other domains. In general,
any type of transform can be applied. For example, in some
embodiments, a time-frequency transformation is applied to the
feature values. In some embodiments, a spatial-frequency
transformation is applied to the feature values. In some
embodiments, the feature values are converted to a different domain
by applying a Fast Fourier Transform (FFT), a Discrete Cosine
Transform (DCT), or both. Once converted, the values for the set of
frames over time are represented as a distribution of frequency
components. In some embodiments, objects in the frames are
segmented and the transformations are applied to these segments. In
some embodiments, regions in the frames are segmented and the
transformations are applied to these segments.
[0070] In some embodiments, each video fingerprint corresponds to a
pre-defined frame rate (e.g., 8 frames per second, 16 frames per
second, 32 frames per second, etc.). For example, at 16 frames per
second, a video fingerprint of a content item can correspond to a
series of 16 frames and can represent one second of video in the
content item. In this example, each of the 16 frames corresponding
to the video fingerprint may be represented as a set of 64 bits or
a 64-bit integer. In various embodiments, the video fingerprinting
module 306 can perform generally known interpolation techniques so
that the video fingerprint corresponds to the pre-defined frame
rate despite the content item being fingerprinted having a
different frame rate. Such interpolation can be performed in the
frequency domain using the spectral components that were determined
for the set of frames. For example, the interpolation of two frames
may be done by discarding any high frequency coefficients that
exceed a threshold (e.g., low-pass filter) while keeping the
remaining low frequency coefficients.
[0071] The video fingerprinting module 306 can quantize these low
frequency coefficients to generate a set of bits that correspond to
a frame included in the video fingerprint. As mentioned, in some
embodiments, the video fingerprint corresponds to a sequence of
frames and each frame is represented as a set of 64 bits or a 64
bit integer. In some embodiments, if applying an 8-point FFT to the
set of frames, the video fingerprinting module 306 can quantize
four of the low frequency components to generate the respective 64
bits that represent each frame in the set of frames. To compute the
next video fingerprint, the video fingerprinting module 306 can
shift the set of frames by one by discarding the value for the
first frame in the set and appending a corresponding value for the
next frame of the content item. Thus, for example, if the initial
set of frames included values for frames 1 to 8, then the shifted
set of frames will include values for frames 2 to 9. The video
fingerprinting module 306 can then generate another video
fingerprint using the shifted set of frames as described above. In
various embodiments, the video fingerprinting module 306 continues
shifting the set of frames to generate video fingerprints until the
last frame in the content item (e.g., end of the live content
stream or end of the on-demand content item file) is reached. Thus,
in such embodiments, fingerprints correspond to overlapping frames
of the content item being fingerprinted. For example, a first
fingerprint can be determined from frames 1 to 16, a second
fingerprint can be determined from frames 2 to 17, a third
fingerprint can be determined from frames 3 to 18, and so on.
[0072] In some embodiments, rather than relying on a single feature
value, a vector of feature values is determined for each frame in
the set of frames and these vectors are used to transform the set
of video frames into the frequency domain. For example, a feature
vector determined for a video frame can describe values of various
features that correspond to the frame. In some embodiments, the
feature values can describe changes (e.g., changes in brightness,
changes in coloration, etc.) between one or more groups of pixels
in the frame. In such embodiments, a first region 606 and a second
region 608 within the first region 606 can be identified around a
pixel 604 in a frame 602, as illustrated in the example of FIG. 6.
Both the first region 606 and the second region 608 can be
segmented into a set of sectors (e.g., 6, 8, 10, etc. sectors). For
example, in FIG. 6, the first region 606 is divided into sectors
a1, a2, a3, a4, a5, a6, a7, and a8 while the second region 608 is
divided into sectors b1, b2, b3, b4, b5, b6, b7, and b8. A feature
value can be computed for each sector. These feature values can be
stored in a matrix 610. Next, a difference is calculated between
the feature value for each inner sector (e.g., b1) and the feature
value for its corresponding outer sector (e.g., a1). These
differences can be stored in a matrix 612 (e.g., f1, f2, . . . ,
f8). In some embodiments, such differences are calculated for each
pixel in the frame 602 and the respective differences are summed to
produce the matrix 612. A matrix 612 can be generated for each
frame in the set of video frames being processed as described
above. As a result, in some embodiments, each frame in the set of
video frames will be represented by a corresponding feature vector
of a set of values (e.g., 8 values). The feature vectors for the
set of video frames can then be interpolated, if needed, and
converted to the frequency domain, for example, by applying a
Discrete Cosine Transform and/or Fast Fourier Transform, as
described above. In some embodiments, some or all of the feature
values included in a feature vector are determined by applying
generally known feature detection approaches, e.g., Oriented FAST
and Rotated BRIEF (ORB).
[0073] In some embodiments, the video fingerprinting module 306
generates more than one fingerprint for each frame. For example, in
some embodiments, the video fingerprinting module 306 horizontally
divides a frame being fingerprinted into a top half and a bottom
half. In such embodiments, a first fingerprint is generated for the
top half of the frame and a second fingerprint is generated for the
bottom half of the frame. For example, the first fingerprint and
the second fingerprint can each be represented using 32 bits. In
one example, such approaches can be used to distinguish content
items that include scrolling text (e.g., end credits). Naturally, a
frame may be divided in a number of different ways (e.g.,
vertically, diagonally, etc.) and respective fingerprints for each
of the divided portions can be generated. In some embodiments,
before fingerprinting content, the video fingerprinting module 306
removes all color information associated with the content and
converts the content into black-and-white, or grayscale,
representation. In some instances, frames in a video may be flipped
(e.g., flipped horizontally, flipped vertically, etc.) from their
original states. Such flipping of frames may be done to prevent
matching content in the video from being identified. Thus, in some
embodiments, when fingerprinting a frame of a video, the video
fingerprinting module 306 generates a fingerprint for the frame in
its original state and one or more separate fingerprints for the
frame in one or more respective flipped states (e.g., flipped
horizontally, flipped vertically, etc.). Video fingerprints that
are generated for content items can be stored and used for
identifying matching content. More details describing the storage
and retrieval of video fingerprints will be provided below with
reference to FIG. 4.
[0074] The thumbnail fingerprinting module 308 can be configured to
obtain, or generate, thumbnail, or image, fingerprints for content
items. In some embodiments, when generating thumbnail fingerprints
for a content item, the thumbnail fingerprinting module 308
captures thumbnail snapshots of frames in the content item at
pre-defined time intervals (e.g., every 1 second, every 3 seconds,
etc.). Such thumbnail snapshots can be used to generate
corresponding thumbnail fingerprints using generally known image
fingerprinting techniques. In some embodiments, each thumbnail
fingerprint is represented using a set of bits (e.g., 32 bits, 64
bits, 128 bits, etc.). In some embodiments, at each pre-defined
time interval, the thumbnail fingerprinting module 308 captures
multiple thumbnail snapshots at one or more scales and/or
resolutions. In such embodiments, separate fingerprints can be
generated for the multiple thumbnail snapshots. Such multiple
fingerprints can be used to identify matching thumbnails between
two content items despite there being distortions in the content
being evaluated. Thumbnail fingerprints that are generated for
content items can be stored and used for identifying matching
content. More details describing the storage and retrieval of
thumbnail fingerprints will be provided below with reference to
FIG. 4.
[0075] In some embodiments, when a content item is to be
fingerprinted, the fingerprinting module 302 generates audio
fingerprints, video fingerprints, and/or thumbnail fingerprints for
the content item. Such fingerprints can be used alone or in
combination to identify other content items that include portions
of content (e.g., audio, video, thumbnails) that match the
fingerprinted content item. In some embodiments, an on-demand
content item can be fingerprinted as soon as the file corresponding
to the on-demand content item is available or uploaded, for
example, to a content provider system (e.g., the social networking
system). In some embodiments, a live content stream is
fingerprinted as soon as data describing the live content stream is
received by the content provider system.
[0076] In some embodiments, the fingerprinting module 302 is
implemented on the content provider system. In such embodiments,
the fingerprinting of the content item is performed by the content
provider system after data describing the content item is received.
In some embodiments, the fingerprinting module 302 is implemented
on a user device. In such embodiments, the fingerprinting of the
content item is performed by the user device as data describing the
content item is sent to the content provider system. In some
embodiments, the distributed fingerprinting module 310 is
configured so that different types of fingerprints are generated by
the user device and the content provider system. For example, in
some embodiments, the distributed fingerprinting module 310 can
instruct the user device to generate one or more types of
fingerprints (e.g., audio fingerprints and/or thumbnail
fingerprints) for a content item being provided to the content
provider system. In such embodiments, the distributed
fingerprinting module 310 can instruct the content provider system
to generate one or more different types of fingerprints (e.g.,
video fingerprints) as the content item is received. Such
distributed fingerprinting can allow for more optimal use of
computing resources.
[0077] In some embodiments, the distributed fingerprinting module
310 can instruct the user device to generate and send one or more
first types of fingerprints (e.g., audio fingerprints) for a
content item being provided to the content provider system. In such
embodiments, if a match between the content item and a reference
content item is identified using the one or more first types of
fingerprints (e.g., audio fingerprints), the distributed
fingerprinting module 310 can instruct the user device to begin
generating and sending one or more second types of fingerprints
(e.g., video fingerprints and/or thumbnail fingerprints) for the
content item being provided to further verify the matched content
using the additional types of fingerprints (e.g., video
fingerprints and/or thumbnail fingerprints). In various
embodiments, fingerprints (e.g., audio fingerprints, video
fingerprints, thumbnail fingerprints) can also be associated with
metadata that provides various information about the respective
content item from which the fingerprints were determined. Such
information can include a title, description, keywords or tags that
correspond to a content item. In some embodiments, the information
can include any text that was extracted from the content item (or
frames corresponding to the content item), for example, using
generally known optical character recognition (OCR) techniques.
[0078] FIG. 4 illustrates an example of a storage module 402,
according to an embodiment of the present disclosure. In some
embodiments, the storage module 206 of FIG. 2 can be implemented as
the storage module 402. As shown in FIG. 4, the storage module 402
can include an indexing module 404 and an optimization module
406.
[0079] The indexing module 404 can be configured to store
fingerprints (e.g., audio fingerprints, video fingerprints,
thumbnail fingerprints) that are generated for content items. In
general, such fingerprints may be stored using any generally known
approach for storing and retrieving data. In some embodiments,
fingerprints generated for live content streams are stored in a
live reference database while fingerprints generated for on-demand
content items are stored in a static reference database. In some
embodiments, fingerprints for content items (e.g., live content
streams and on-demand content items) that were provided (e.g.,
streamed and/or uploaded) within a threshold period of time (e.g.,
within the last 24 hours, 48 hours, etc.) are stored in a real-time
reference database while fingerprints for content items that were
provided beyond this threshold period of time are stored in a
static reference database. In such embodiments, the storage module
402 moves fingerprint data for content items from the real-time
reference database to the static reference database, as needed, to
satisfy the separation of fingerprint data between the two
databases based on the threshold period of time.
[0080] In some embodiments, the indexing module 404 stores
fingerprint data in one or more data structures. The data
structures used may vary depending on the computing resources that
are available for storing and processing fingerprint data. In one
example, one set of computing resources may justify the use of
index data structures while another set of computing resources may
justify the use of inverted index data structures. For example,
audio fingerprints can be stored in a first inverted index data
structure, video fingerprints can be stored in a second inverted
index data structure, and thumbnail fingerprints can be stored in a
third inverted index data structure. As mentioned, separate
inverted index data structures may be used for storing fingerprints
generated for live content streams and on-demand content items.
FIG. 7 illustrates an example inverted index data structure 702. In
this example, the inverted index 702 includes a set of bins 704.
Each bin can reference a set of fingerprinted frames that have been
hashed to that bin. For example, the fingerprinted frames 708 and
710 have both been hashed to the bin 706.
[0081] As mentioned, each fingerprint can correspond to a set of
frames and each frame can be represented as a set of bits, e.g., 64
bits, or an integer. In some embodiments, when inserting a
fingerprinted frame into the inverted index 702, a portion of the
bits corresponding to the fingerprinted frame are used to hash to
one of the bins 704 in the inverted index 702. For example, the
first 24 bits of the 64 bits corresponding to the fingerprinted
frame 708 (e.g., the index portion) can be hashed to the bin 706.
The fingerprinted frame 708 can then be added to a list 712 of
fingerprinted frames that have been hashed to the bin 706. In some
embodiments, when adding the fingerprinted frame 708 to the list
712, the remaining portion of the bits are stored. Thus, in this
example, the residual 40 bits of the 64 bits corresponding to the
fingerprinted frame 708 are stored. In some embodiments, the
fingerprinted frame 708 is stored with information describing the
content item from which the fingerprinted frame was generated
(e.g., file identifier, stream identifier, etc.) and an offset
(e.g., time stamp, frame number, etc.) that indicates the portion
of the content item from which the fingerprint was generated.
[0082] In some embodiments, multiple inverted indexes can be
utilized for fingerprint storage and matching. For example, a first
portion of the bits corresponding to a fingerprinted frame can be
hashed to one of the bins of a first inverted index. This bin in
the first inverted index can reference a second inverted index. In
this example, a second portion of the bits corresponding to the
fingerprinted frame can be hashed to a bin in the second inverted
index to identify a list of fingerprinted frames that have been
hashed to that bin. The set of bits corresponding to the
fingerprinted frame (the entire set of bits or the remaining
portion of bits) can be added to this list in the second inverted
index. For example, the first 24 bits of a 64 bit fingerprinted
frame may be hashed to a bin in a first inverted index to identify
a second inverted index. In this example, the next 20 bits of the
64 bit fingerprinted frame may be hashed to a bin in the second
inverted index to identify a list of fingerprinted frames
referenced by the bin. Here, the remaining 20 bits of the 64 bit
fingerprinted frame (or all of the 64 bits) can be stored in the
list. The fingerprinted frame can be stored in the second inverted
index with information describing the content item from which the
fingerprinted frame was generated (e.g., file identifier, stream
identifier, etc.) and an offset (e.g., time stamp, frame number,
etc.) that indicates the portion of the content item from which the
fingerprinted frame was generated.
[0083] The optimization module 406 can be configured to manage the
inverted index data structures that are utilized for fingerprint
storage and matching. For example, in some embodiments, the
optimization module 406 can automatically update, or clean up, the
inverted indexes to remove entries that correspond to content items
that have been removed from the content provider system. In some
embodiments, the optimization module 406 can automatically update,
or clean up, the inverted indexes to remove entries that have been
stored for a threshold period of time. In some embodiments, the
optimization module 406 can sort the inverted indexes to achieve a
desired organization. In one example, the optimization module 406
can sort entries in the inverted indexes so that similar
fingerprinted frames (e.g., fingerprinted frames that are a
threshold Hamming distance of one another) are clustered, or
organized, into the same (or nearby) chunks or bins.
[0084] FIG. 5 illustrates an example of a matching module 502,
according to an embodiment of the present disclosure. In some
embodiments, the matching module 208 of FIG. 2 can be implemented
as the matching module 502. As shown in FIG. 5, the matching module
502 can include a fingerprint matching module 504, a combined
matching module 506, a live processing module 508, and a distortion
module 510.
[0085] The fingerprint matching module 504 can be configured to
identify any portions of content in a first (or test) content item
that matches portions of content in one or more second (or
reference) content items. In various embodiments, the fingerprint
matching module 504 can evaluate the test content item using a set
of fingerprints (e.g., audio fingerprints, video fingerprints,
thumbnail fingerprints) corresponding to the test content item and
these fingerprints can be used to identify one or more reference
content items to be analyzed. Such reference content items may have
been identified, or designated, as being protected (or
copyrighted). In general, test content items that include any
content that matches content in a reference content item can be
flagged and various actions can be taken. Reference content items
can be identified, for example, using an inverted index data
structure, as described above.
[0086] For example, as illustrated in FIG. 8A, the fingerprint
matching module 504 can obtain a video fingerprint that was
generated from the test content item. The video fingerprint can
correspond to a set of frames (e.g., 16 frames) and each frame can
be represented as a set of bits (e.g., 64 bits). In some
embodiments, a first portion of a frame 804 in the fingerprint
(e.g., the first 24 bits) can be used to hash to a bin 806 in an
inverted index 802 and a second portion of the frame 804 (e.g., the
remaining 40 bits) can be used to verify matches between frames. As
mentioned, the inverted index 802 includes a set of bins and each
bin can reference a set of fingerprinted frames that have been
hashed to that bin. For example, in FIG. 8A, the bin 806 references
a fingerprinted frame 808 and a fingerprinted frame 810. In this
example, both the fingerprinted frame 808 and the fingerprinted
frame 810 are candidates matches. The fingerprint matching module
504 can evaluate each of the fingerprinted frames 808, 810 that
correspond to the bin 806 to determine whether the fingerprinted
frames match the frame 804. In some embodiments, the fingerprint
matching module 504 determines a Hamming distance between a set of
bits corresponding to a first frame and a set of bits corresponding
to a second frame. In such embodiments, the fingerprint matching
module 504 determines a match between the first frame and the
second frame when the Hamming distance satisfies a threshold value.
Thus, for example, the fingerprint matching module 504 can
determine a Hamming distance between the set of bits corresponding
to the frame 804 and the set of bits corresponding to the
fingerprinted frame 808. If this Hamming distance satisfies a
threshold value, then a match between the frame 804 and the
fingerprinted frame 808 is identified. The same process can be
applied to the remaining fingerprinted frames (e.g., the
fingerprinted frame 810) that are referenced by the bin 806 to
which the frame 804 was hashed to identify any other matches.
[0087] When a match between the frame 804 of the test content item
and a fingerprinted frame (e.g., the fingerprinted frame 808) of
the reference content item has been identified, the fingerprint
matching module 504 can evaluate the reference content item from
which the matching fingerprinted frame 808 was generated to
determine the extent, or boundary, of the matching content between
the test content item and the reference content item. As mentioned,
each frame stored in the inverted index 802 can also indicate the
reference content item from which the fingerprinted frame was
generated (e.g., a file name, stream identifier, etc.) and an
offset that indicates the portion of the reference content item to
which the fingerprinted frame corresponds. Using such information,
the fingerprint matching module 504 can access a set of
fingerprinted frames 840 that were chronologically generated for
the entirety of the reference content item, as illustrated in the
example FIG. 8B. The fingerprint matching module 504 can also
access a set of fingerprinted frames 860 that correspond to the
test content item. In some embodiments, the fingerprint matching
module 504 processes the test content item and the reference
content item in chunks (e.g., one second chunks). Thus, for
example, if each fingerprint corresponds to 16 frames per second,
then the fingerprint matching module 504 processes 16 frames of
content per second.
[0088] As shown in FIG. 8B, the fingerprint matching module 504 can
evaluate each fingerprinted frame that precedes the matching
fingerprinted frame 808 of the reference content item against each
corresponding fingerprinted frame that precedes the fingerprinted
frame 804 of the test content item. Thus, for example, the
fingerprint matching module 504 can compute a Hamming distance
between the fingerprinted frame 820 of the reference content item
and the fingerprinted frame 824 of the test content item. If the
Hamming distance satisfies a threshold value, then a content match
is found. The fingerprint matching module 504 can continue such
matching with each preceding frame until no match is found or until
the beginning of the reference content item and/or the test content
item is reached. Similarly, the fingerprint matching module 504 can
evaluate each fingerprinted frame subsequent to the matching
fingerprint 808 in the reference content item against each
corresponding fingerprinted frame that is subsequent to the
matching fingerprinted frame 804 in the test content item. Thus,
for example, the fingerprint matching module 504 can compute a
Hamming distance between the fingerprinted frame 822 of the
reference content item and the fingerprinted frame 826 of the test
content item. If the Hamming distance satisfies a threshold value,
then a content match is found. The fingerprint matching module 504
can continue such matching with each subsequent frame until no
match is found or until the end of the reference content item
and/or the test content item is reached. Once such matching is
complete, the fingerprint matching module 504 can identify which
portion 832 of the test content item matches a boundary 830 of the
reference content item. This matching process can be applied to
find matches between audio fingerprints of a test content item and
a reference content item, video fingerprints of a test content item
and a reference content item, and/or thumbnail fingerprints of a
test content item and a reference content item. The matching
process described in reference to FIGS. 8A-B is just one example
approach for determining matching content between two content items
and, naturally, other approaches are possible. In some embodiments,
the matching process is optimized so that not all fingerprinted
frames of a test content item and a reference content item need to
be evaluated to determine a match. For example, upon identifying a
match between a first fingerprinted frame of a test content item
and a first fingerprinted frame of a reference content item, the
fingerprint matching module 504 can skip one or more intermediate
frames (e.g., a threshold number of fingerprinted frames) in the
test content item and the reference content item, and then evaluate
a second fingerprinted frame of the test content item and a second
fingerprinted frame of the reference content item. If both the
first fingerprinted frames and the second fingerprinted frames
match, then an assumption is made that the one or more intermediate
frames of the test content item and the reference content item also
match. In some embodiments, the matching process is two-tiered in
which the first verification step is optimized to determine a match
when a set of first fingerprinted frames match and a second set of
fingerprinted frames match while skipping the evaluation of a
threshold number of intermediate fingerprinted frames in the
content items. In such embodiments, each of the intermediate
fingerprinted frames are also evaluated individually during a
second verification step to confirm the full length of the
match.
[0089] In some embodiments, information describing the matching
portions 830 and 832 is provided to various personnel for further
review. In some embodiments, if the matching portions 830 and 832
satisfy a threshold length of time (e.g., 30 seconds), then the
fingerprint matching module 504 can automatically flag the test
content item for further review. In some embodiments, if the
matching portions 830 and 832 satisfy a threshold length of time
(e.g., 30 seconds), then the fingerprint matching module 504 can
automatically prevent users from accessing the test content item.
In some embodiments, the fingerprint matching module 504 may
determine that the test content item and the reference content item
are duplicates (i.e., all of the test content item matches all of
the reference content item). In such embodiments, the test content
item may automatically be deleted.
[0090] The combined matching module 506 can be configured to
utilize multiple types of fingerprints (e.g., audio, video,
thumbnail) to identify matching content between a test content item
and a reference content item. For example, in some embodiments, the
combined matching module 506 can determine matching content between
a test content item and a reference content item using audio
fingerprints, as described above. In such embodiments, the combined
matching module 506 supplements the matching using other types of
fingerprints (e.g., video fingerprints and/or thumbnail
fingerprints) when no matches are found using the audio
fingerprints for a threshold period of time and/or a threshold
number of frames. In some embodiments, the combined matching module
506 can verify content matches that were determined using audio
fingerprints by additional use of corresponding video fingerprints
(or thumbnail fingerprints). Such verification can be useful, for
example, to distinguish between a video ad that includes
copyrighted music over a music video. Similarly, in some
embodiments, the combined matching module 506 can verify content
matches that were determined using video fingerprints by additional
use of corresponding audio fingerprints (or thumbnail
fingerprints). In various embodiments, audio fingerprints and video
fingerprints are generated at a pre-defined frame rate. As a
result, the combined matching module 506 can easily cross-reference
between an audio fingerprint and a video fingerprint for a given
frame.
[0091] In some embodiments, a user device that is providing a
content item to the content provider system can be instructed to
generate and send thumbnail fingerprints of the content item. In
such embodiments, the combined matching module 506 can utilize the
thumbnail fingerprints to identify matching content between the
content item and a reference content item. If a match is found, the
user device can be instructed to generate and send other types of
fingerprints of the content item (e.g., audio fingerprints and/or
video fingerprints). The combined matching module 506 can utilize
the other types of fingerprints to verify the frame matches that
were determined using the thumbnail fingerprints. For example, if a
match is determined between a frame of the content item and a frame
of a reference content item using thumbnail fingerprints, then the
combined fingerprint matching module 506 can confirm the match
using video fingerprints that correspond to the matching frames of
the content item and the reference content item. In some
embodiments, if a match is found using the thumbnail fingerprints,
the content provider system can begin generating other types of
fingerprints (e.g., audio fingerprints and/or video fingerprints)
for the content item for verification purposes.
[0092] Generally, when evaluating content of an on-demand content
item, the matching module 502 is able to identify one or more
reference content items and evaluate these reference content items
against the on-demand content item to identify matching content. In
some embodiments, the matching module 502 can be configured to
process live content streams differently for purposes of content
matching. For example, in some embodiments, the live processing
module 508 can be configured to process a live content stream being
received in fixed portions using a sliding window. In some
embodiments, the live processing module 508 can define the sliding
window to include frames of the live content stream that correspond
to a fixed length of time (e.g., the last 20 seconds of content) or
a fixed number of frames (e.g., 16 frames). FIG. 9A illustrates an
example diagram of a live content stream 902 being received by the
content provider system from a user device. In the example of FIG.
9A, a sliding window 904 corresponds to 20 seconds of the live
content stream 902 as defined by a frame 906 and a frame 908. In
some embodiments, when a live content stream is being received, the
live processing module 508 buffers the live content stream until
the length of the sliding window 904 is satisfied. For example, if
the sliding window corresponds to a length of 20 seconds, then the
live processing module 508 buffers 20 seconds of the live content
stream. Once buffered, the live processing module 508 fingerprints
a portion of the content in the sliding window 904 (e.g., the last
one second of the content in the sliding window 904), as described
above. Once fingerprinted, the live processing module 508 can
determine whether the fingerprinted portion of the live content
stream matches any reference content items. As described above, the
matching process will attempt to determine a boundary of the
matching content by evaluating the previously received frames in
the live content stream 902. In this example, when another one
second of the live content stream is received, the sliding window
advances to encompass the most recent 20 seconds of the live
content stream. FIG. 9B illustrates an example diagram of the live
content stream 912 after another one second of the live content
stream is received. In the example of FIG. 9B, the sliding window
914 has advanced to the most recent 20 seconds of the live content
stream and is now bounded by frames 906 and 918. Similarly, in this
example, the live processing module 508 fingerprints the last one
second of the live content stream that was received and determines
whether the fingerprinted portion matches any reference content
items. FIG. 9C illustrates an example diagram of the live content
stream 922 after another one second of the live content stream is
received. In the example of FIG. 9C, the sliding window 924 has
advanced to the most recent 20 seconds of the live content stream
and is now bounded by frames 906 and 928. Similarly, in this
example, the live processing module 508 fingerprints the last one
second of the live content stream that was received and determines
whether the fingerprinted portion matches any reference content
items. This approach of processing a live content stream using a
sliding window allows for optimally detecting matching content in
reference content items. This approach can also address situations
in which receipt of a reference live content stream is delayed. In
such instances, the content provider system is able to determine
matching content between a test live content stream and the delayed
reference live content stream. In some embodiments, the sliding
window can be extended to facilitate identification of content that
includes repeating patterns.
[0093] In some instances, a live content stream may be susceptible
to distortions which can complicate the matching process. For
example, a user may provide a live content stream of a concert that
was captured using a computing device. This live content stream may
be captured from a certain angle and/or zoom level. The captured
content may also be susceptible to various rotations that result
from shaking of the computing device. Such distortions may make it
difficult to find an exact match against a reference live content
stream (i.e., a protected, or copyrighted, stream) that was
provided by an authorized broadcaster, for example. In some
embodiments, the distortion module 510 is configured to apply
various approaches to facilitate content matching despite such
distortions.
[0094] For example, in some embodiments, when attempting to find
matches for a fingerprinted frame of a live content stream, the
distortion module 510 can generate a set of distorted fingerprinted
frames and attempt to find matches using each of the distorted
fingerprinted frames. Thus, in the example above, when attempting
to find matches for a fingerprinted frame that corresponds to the
last one second of a live content stream, the distortion module 510
permutes the index portion of the set of bits corresponding to the
fingerprinted frame (e.g., the first 24 bits). In some embodiments,
this index portion is used to find reference content items in one
or more inverted indexes, as described above. In some embodiments,
the distortion module 510 permutes the index portion of the
fingerprinted frame one bit at a time. For example, assume that the
frame is represented using six bits "010111" and the index portion
is represented using the first three bits, e.g., "010". In this
example, the distortion module 510 can permute the index portion
one bit at a time to generate the following set of distortions:
"000", "011", "110". These distortions can be prepended to the
remaining three bits corresponding to the frame, e.g., "111" to
produce the following set of distorted fingerprinted frames:
"000111", "001111", "011111", "100111", "101111", "110111", and
"111111". Each of these distorted fingerprinted frames can be used
to identify one or more reference content items and determine what
portions of those reference content items include matching content,
as described above. In some embodiments, the distortion module 510
permutes the index portion of the fingerprinted frame multiple bits
(e.g., two bits) at a time to generate additional distorted
fingerprints frames to identify matching content. In example above,
the distortion module 510 can permute the index portion "010" two
bits at a time to generate the following set of distortions: "001",
"111", and "100". In some embodiments, rather than only distorting
the index portion, the distortion module 510 permutes all of the
bits corresponding to a fingerprinted frame. In some embodiments,
the distortion module 510 throttles the portion (or number of bits)
that are permuted in a set of bits. For example, in some
embodiments, the portion (or number of bits) permuted when
attempting to find matches for a fingerprinted frame can vary
depending on the amount of central processing unit (CPU) usage. In
one example, the distortion module 510 can permute the first 24
bits of the frame when the CPU usage is within a threshold and,
when the CPU usage has reached the threshold, the distortion module
510 can reduce the permutations to the first 16 bits of the
frame.
[0095] Such permutations generally increase the amount of content
to be evaluated when determining matching portions of two content
items thereby accounting for distortions that may exist in the test
content item being analyzed. However, in some instances, various
approaches to regulate the amount of content to be evaluated may be
applied for purposes of improving system performance. For example,
in some embodiments, distortions may be generated and tested in
stages until a threshold central processing unit (CPU) usage is
reached (e.g., 70 percent, 75 percent, etc.). For example, a
fingerprinted frame may first be evaluated without any distortions.
If no matches are found, then the fingerprinted frame may be
distorted by permuting one bit at a time. If no matches are found
using the permutations, then the fingerprinted frame may be
distorted by permuting two bits at a time. In some embodiments,
distortions may be generated and tested in stages until a threshold
query time (e.g., 150 milliseconds, 200 milliseconds, etc.) is
reached. In such embodiments, the matching process is discontinued
when the threshold query time is reached. As mentioned, a
fingerprint can correspond to a series of frames (e.g., 16 frames)
over some length of content (e.g., one second of content). In some
embodiments, instead of evaluating each of the 16 fingerprinted
frames corresponding to the fingerprint, the distortion module 510
can be configured to skip the evaluation of one or more of
fingerprinted frames (e.g., skip 15 frames and evaluate only the
16.sup.th frame corresponding to the fingerprint). In some
embodiments, when evaluating a fingerprint, the matching module 502
can be configured to segment the fingerprint into a set of smaller
chunks and each of the chunks in the set can be processed in
parallel using generally known parallel processing techniques.
[0096] FIG. 10 illustrates an example process 1000 for
fingerprinting content, according to various embodiments of the
present disclosure. It should be appreciated that there can be
additional, fewer, or alternative steps performed in similar or
alternative orders, or in parallel, within the scope of the various
embodiments discussed herein unless otherwise stated.
[0097] At block 1002, a test content item having a plurality of
video frames is obtained. At block 1004, at least one video
fingerprint is generated based on a set of video frames
corresponding to the test content item. At block 1006, at least one
reference content item is determined using at least a portion of
the video fingerprint. At block 1008, a determination is made that
at least one portion of the test content item matches at least one
portion of the reference content item based at least in part on the
video fingerprint of the test content item and one or more video
fingerprints of the reference content item.
[0098] FIG. 11 illustrates an example process 1100 for matching
content using different types of fingerprints, according to various
embodiments of the present disclosure. It should be appreciated
that there can be additional, fewer, or alternative steps performed
in similar or alternative orders, or in parallel, within the scope
of the various embodiments discussed herein unless otherwise
stated.
[0099] At block 1102, at least one portion of a test content item
is evaluated with at least one portion of a reference content item
using one or more first fingerprints of the test content item and
one or more first fingerprints of the reference content item. The
first fingerprints correspond to a first type of media. At block
1104, a determination is made that at least one verification
criteria is satisfied. At block 1106, the portion of the test
content is evaluated with the portion of the reference content
using one or more second fingerprints of the test content item and
one or more second fingerprints of the reference content item. The
second fingerprints correspond to a second type of media that is
different from the first type of media.
[0100] FIG. 12 illustrates an example process 1200 for matching
content using distorted fingerprints, according to various
embodiments of the present disclosure. It should be appreciated
that there can be additional, fewer, or alternative steps performed
in similar or alternative orders, or in parallel, within the scope
of the various embodiments discussed herein unless otherwise
stated.
[0101] At block 1202, at least one fingerprint is generated based
on a set of frames corresponding to a test content item. At block
1204, a set of distorted fingerprints are generated using at least
a portion of the fingerprint. At block 1206, one or more reference
content items are determined using the set of distorted
fingerprints, wherein the test content item is evaluated against at
least one reference content item to identify matching content.
[0102] It is contemplated that there can be many other uses,
applications, and/or variations associated with the various
embodiments of the present disclosure. For example, in some cases,
user can choose whether or not to opt-in to utilize the disclosed
technology. The disclosed technology can also ensure that various
privacy settings and preferences are maintained and can prevent
private information from being divulged. In another example,
various embodiments of the present disclosure can learn, improve,
and/or be refined over time.
Social Networking System--Example Implementation
[0103] FIG. 13 illustrates a network diagram of an example system
1300 that can be utilized in various scenarios, in accordance with
an embodiment of the present disclosure. The system 1300 includes
one or more user devices 1310, one or more external systems 1320, a
social networking system (or service) 1330, and a network 1350. In
an embodiment, the social networking service, provider, and/or
system discussed in connection with the embodiments described above
may be implemented as the social networking system 1330. For
purposes of illustration, the embodiment of the system 1300, shown
by FIG. 13, includes a single external system 1320 and a single
user device 1310. However, in other embodiments, the system 1300
may include more user devices 1310 and/or more external systems
1320. In certain embodiments, the social networking system 1330 is
operated by a social network provider, whereas the external systems
1320 are separate from the social networking system 1330 in that
they may be operated by different entities. In various embodiments,
however, the social networking system 1330 and the external systems
1320 operate in conjunction to provide social networking services
to users (or members) of the social networking system 1330. In this
sense, the social networking system 1330 provides a platform or
backbone, which other systems, such as external systems 1320, may
use to provide social networking services and functionalities to
users across the Internet.
[0104] The user device 1310 comprises one or more computing devices
(or systems) that can receive input from a user and transmit and
receive data via the network 1350. In one embodiment, the user
device 1310 is a conventional computer system executing, for
example, a Microsoft Windows compatible operating system (OS),
Apple OS X, and/or a Linux distribution. In another embodiment, the
user device 1310 can be a computing device or a device having
computer functionality, such as a smart-phone, a tablet, a personal
digital assistant (PDA), a mobile telephone, a laptop computer, a
wearable device (e.g., a pair of glasses, a watch, a bracelet,
etc.), a camera, an appliance, etc. The user device 1310 is
configured to communicate via the network 1350. The user device
1310 can execute an application, for example, a browser application
that allows a user of the user device 1310 to interact with the
social networking system 1330. In another embodiment, the user
device 1310 interacts with the social networking system 1330
through an application programming interface (API) provided by the
native operating system of the user device 1310, such as iOS and
ANDROID. The user device 1310 is configured to communicate with the
external system 1320 and the social networking system 1330 via the
network 1350, which may comprise any combination of local area
and/or wide area networks, using wired and/or wireless
communication systems.
[0105] In one embodiment, the network 1350 uses standard
communications technologies and protocols. Thus, the network 1350
can include links using technologies such as Ethernet, 802.11,
worldwide interoperability for microwave access (WiMAX), 3G, 4G,
CDMA, GSM, LTE, digital subscriber line (DSL), etc. Similarly, the
networking protocols used on the network 1350 can include
multiprotocol label switching (MPLS), transmission control
protocol/Internet protocol (TCP/IP), User Datagram Protocol (UDP),
hypertext transport protocol (HTTP), simple mail transfer protocol
(SMTP), file transfer protocol (FTP), and the like. The data
exchanged over the network 1350 can be represented using
technologies and/or formats including hypertext markup language
(HTML) and extensible markup language (XML). In addition, all or
some links can be encrypted using conventional encryption
technologies such as secure sockets layer (SSL), transport layer
security (TLS), and Internet Protocol security (IPsec).
[0106] In one embodiment, the user device 1310 may display content
from the external system 1320 and/or from the social networking
system 1330 by processing a markup language document 1314 received
from the external system 1320 and from the social networking system
1330 using a browser application 1312. The markup language document
1314 identifies content and one or more instructions describing
formatting or presentation of the content. By executing the
instructions included in the markup language document 1314, the
browser application 1312 displays the identified content using the
format or presentation described by the markup language document
1314. For example, the markup language document 1314 includes
instructions for generating and displaying a web page having
multiple frames that include text and/or image data retrieved from
the external system 1320 and the social networking system 1330. In
various embodiments, the markup language document 1314 comprises a
data file including extensible markup language (XML) data,
extensible hypertext markup language (XHTML) data, or other markup
language data. Additionally, the markup language document 1314 may
include JavaScript Object Notation (JSON) data, JSON with padding
(JSONP), and JavaScript data to facilitate data-interchange between
the external system 1320 and the user device 1310. The browser
application 1312 on the user device 1310 may use a JavaScript
compiler to decode the markup language document 1314.
[0107] The markup language document 1314 may also include, or link
to, applications or application frameworks such as FLASH.TM. or
Unity.TM. applications, the Silverlight.TM. application framework,
etc.
[0108] In one embodiment, the user device 1310 also includes one or
more cookies 1316 including data indicating whether a user of the
user device 1310 is logged into the social networking system 1330,
which may enable modification of the data communicated from the
social networking system 1330 to the user device 1310.
[0109] The external system 1320 includes one or more web servers
that include one or more web pages 1322a, 1322b, which are
communicated to the user device 1310 using the network 1350. The
external system 1320 is separate from the social networking system
1330. For example, the external system 1320 is associated with a
first domain, while the social networking system 1330 is associated
with a separate social networking domain. Web pages 1322a, 1322b,
included in the external system 1320, comprise markup language
documents 1314 identifying content and including instructions
specifying formatting or presentation of the identified content. As
discussed previously, it should be appreciated that there can be
many variations or other possibilities.
[0110] The social networking system 1330 includes one or more
computing devices for a social network, including a plurality of
users, and providing users of the social network with the ability
to communicate and interact with other users of the social network.
In some instances, the social network can be represented by a
graph, i.e., a data structure including edges and nodes. Other data
structures can also be used to represent the social network,
including but not limited to databases, objects, classes, meta
elements, files, or any other data structure. The social networking
system 1330 may be administered, managed, or controlled by an
operator. The operator of the social networking system 1330 may be
a human being, an automated application, or a series of
applications for managing content, regulating policies, and
collecting usage metrics within the social networking system 1330.
Any type of operator may be used.
[0111] Users may join the social networking system 1330 and then
add connections to any number of other users of the social
networking system 1330 to whom they desire to be connected. As used
herein, the term "friend" refers to any other user of the social
networking system 1330 to whom a user has formed a connection,
association, or relationship via the social networking system 1330.
For example, in an embodiment, if users in the social networking
system 1330 are represented as nodes in the social graph, the term
"friend" can refer to an edge formed between and directly
connecting two user nodes.
[0112] Connections may be added explicitly by a user or may be
automatically created by the social networking system 1330 based on
common characteristics of the users (e.g., users who are alumni of
the same educational institution). For example, a first user
specifically selects a particular other user to be a friend.
Connections in the social networking system 1330 are usually in
both directions, but need not be, so the terms "user" and "friend"
depend on the frame of reference. Connections between users of the
social networking system 1330 are usually bilateral ("two-way"), or
"mutual," but connections may also be unilateral, or "one-way." For
example, if Bob and Joe are both users of the social networking
system 1330 and connected to each other, Bob and Joe are each
other's connections. If, on the other hand, Bob wishes to connect
to Joe to view data communicated to the social networking system
1330 by Joe, but Joe does not wish to form a mutual connection, a
unilateral connection may be established. The connection between
users may be a direct connection; however, some embodiments of the
social networking system 1330 allow the connection to be indirect
via one or more levels of connections or degrees of separation.
[0113] In addition to establishing and maintaining connections
between users and allowing interactions between users, the social
networking system 1330 provides users with the ability to take
actions on various types of items supported by the social
networking system 1330. These items may include groups or networks
(i.e., social networks of people, entities, and concepts) to which
users of the social networking system 1330 may belong, events or
calendar entries in which a user might be interested,
computer-based applications that a user may use via the social
networking system 1330, transactions that allow users to buy or
sell items via services provided by or through the social
networking system 1330, and interactions with advertisements that a
user may perform on or off the social networking system 1330. These
are just a few examples of the items upon which a user may act on
the social networking system 1330, and many others are possible. A
user may interact with anything that is capable of being
represented in the social networking system 1330 or in the external
system 1320, separate from the social networking system 1330, or
coupled to the social networking system 1330 via the network
1350.
[0114] The social networking system 1330 is also capable of linking
a variety of entities. For example, the social networking system
1330 enables users to interact with each other as well as external
systems 1320 or other entities through an API, a web service, or
other communication channels. The social networking system 1330
generates and maintains the "social graph" comprising a plurality
of nodes interconnected by a plurality of edges. Each node in the
social graph may represent an entity that can act on another node
and/or that can be acted on by another node. The social graph may
include various types of nodes. Examples of types of nodes include
users, non-person entities, content items, web pages, groups,
activities, messages, concepts, and any other things that can be
represented by an object in the social networking system 1330. An
edge between two nodes in the social graph may represent a
particular kind of connection, or association, between the two
nodes, which may result from node relationships or from an action
that was performed by one of the nodes on the other node. In some
cases, the edges between nodes can be weighted. The weight of an
edge can represent an attribute associated with the edge, such as a
strength of the connection or association between nodes. Different
types of edges can be provided with different weights. For example,
an edge created when one user "likes" another user may be given one
weight, while an edge created when a user befriends another user
may be given a different weight.
[0115] As an example, when a first user identifies a second user as
a friend, an edge in the social graph is generated connecting a
node representing the first user and a second node representing the
second user. As various nodes relate or interact with each other,
the social networking system 1330 modifies edges connecting the
various nodes to reflect the relationships and interactions.
[0116] The social networking system 1330 also includes
user-generated content, which enhances a user's interactions with
the social networking system 1330. User-generated content may
include anything a user can add, upload, send, or "post" to the
social networking system 1330. For example, a user communicates
posts to the social networking system 1330 from a user device 1310.
Posts may include data such as status updates or other textual
data, location information, images such as photos, videos, links,
music or other similar data and/or media. Content may also be added
to the social networking system 1330 by a third party. Content
"items" are represented as objects in the social networking system
1330. In this way, users of the social networking system 1330 are
encouraged to communicate with each other by posting text and
content items of various types of media through various
communication channels. Such communication increases the
interaction of users with each other and increases the frequency
with which users interact with the social networking system
1330.
[0117] The social networking system 1330 includes a web server
1332, an API request server 1334, a user profile store 1336, a
connection store 1338, an action logger 1340, an activity log 1342,
and an authorization server 1344. In an embodiment of the
invention, the social networking system 1330 may include
additional, fewer, or different components for various
applications. Other components, such as network interfaces,
security mechanisms, load balancers, failover servers, management
and network operations consoles, and the like are not shown so as
to not obscure the details of the system.
[0118] The user profile store 1336 maintains information about user
accounts, including biographic, demographic, and other types of
descriptive information, such as work experience, educational
history, hobbies or preferences, location, and the like that has
been declared by users or inferred by the social networking system
1330. This information is stored in the user profile store 1336
such that each user is uniquely identified. The social networking
system 1330 also stores data describing one or more connections
between different users in the connection store 1338. The
connection information may indicate users who have similar or
common work experience, group memberships, hobbies, or educational
history. Additionally, the social networking system 1330 includes
user-defined connections between different users, allowing users to
specify their relationships with other users. For example,
user-defined connections allow users to generate relationships with
other users that parallel the users' real-life relationships, such
as friends, co-workers, partners, and so forth. Users may select
from predefined types of connections, or define their own
connection types as needed. Connections with other nodes in the
social networking system 1330, such as non-person entities,
buckets, cluster centers, images, interests, pages, external
systems, concepts, and the like are also stored in the connection
store 1338.
[0119] The social networking system 1330 maintains data about
objects with which a user may interact. To maintain this data, the
user profile store 1336 and the connection store 1338 store
instances of the corresponding type of objects maintained by the
social networking system 1330. Each object type has information
fields that are suitable for storing information appropriate to the
type of object. For example, the user profile store 1336 contains
data structures with fields suitable for describing a user's
account and information related to a user's account. When a new
object of a particular type is created, the social networking
system 1330 initializes a new data structure of the corresponding
type, assigns a unique object identifier to it, and begins to add
data to the object as needed. This might occur, for example, when a
user becomes a user of the social networking system 1330, the
social networking system 1330 generates a new instance of a user
profile in the user profile store 1336, assigns a unique identifier
to the user account, and begins to populate the fields of the user
account with information provided by the user.
[0120] The connection store 1338 includes data structures suitable
for describing a user's connections to other users, connections to
external systems 1320 or connections to other entities. The
connection store 1338 may also associate a connection type with a
user's connections, which may be used in conjunction with the
user's privacy setting to regulate access to information about the
user. In an embodiment of the invention, the user profile store
1336 and the connection store 1338 may be implemented as a
federated database.
[0121] Data stored in the connection store 1338, the user profile
store 1336, and the activity log 1342 enables the social networking
system 1330 to generate the social graph that uses nodes to
identify various objects and edges connecting nodes to identify
relationships between different objects. For example, if a first
user establishes a connection with a second user in the social
networking system 1330, user accounts of the first user and the
second user from the user profile store 1336 may act as nodes in
the social graph. The connection between the first user and the
second user stored by the connection store 1338 is an edge between
the nodes associated with the first user and the second user.
Continuing this example, the second user may then send the first
user a message within the social networking system 1330. The action
of sending the message, which may be stored, is another edge
between the two nodes in the social graph representing the first
user and the second user. Additionally, the message itself may be
identified and included in the social graph as another node
connected to the nodes representing the first user and the second
user.
[0122] In another example, a first user may tag a second user in an
image that is maintained by the social networking system 1330 (or,
alternatively, in an image maintained by another system outside of
the social networking system 1330). The image may itself be
represented as a node in the social networking system 1330. This
tagging action may create edges between the first user and the
second user as well as create an edge between each of the users and
the image, which is also a node in the social graph. In yet another
example, if a user confirms attending an event, the user and the
event are nodes obtained from the user profile store 1336, where
the attendance of the event is an edge between the nodes that may
be retrieved from the activity log 1342. By generating and
maintaining the social graph, the social networking system 1330
includes data describing many different types of objects and the
interactions and connections among those objects, providing a rich
source of socially relevant information.
[0123] The web server 1332 links the social networking system 1330
to one or more user devices 1310 and/or one or more external
systems 1320 via the network 1350. The web server 1332 serves web
pages, as well as other web-related content, such as Java,
JavaScript, Flash, XML, and so forth. The web server 1332 may
include a mail server or other messaging functionality for
receiving and routing messages between the social networking system
1330 and one or more user devices 1310. The messages can be instant
messages, queued messages (e.g., email), text and SMS messages, or
any other suitable messaging format.
[0124] The API request server 1334 allows one or more external
systems 1320 and user devices 1310 to call access information from
the social networking system 1330 by calling one or more API
functions. The API request server 1334 may also allow external
systems 1320 to send information to the social networking system
1330 by calling APIs. The external system 1320, in one embodiment,
sends an API request to the social networking system 1330 via the
network 1350, and the API request server 1334 receives the API
request. The API request server 1334 processes the request by
calling an API associated with the API request to generate an
appropriate response, which the API request server 1334
communicates to the external system 1320 via the network 1350. For
example, responsive to an API request, the API request server 1334
collects data associated with a user, such as the user's
connections that have logged into the external system 1320, and
communicates the collected data to the external system 1320. In
another embodiment, the user device 1310 communicates with the
social networking system 1330 via APIs in the same manner as
external systems 1320.
[0125] The action logger 1340 is capable of receiving
communications from the web server 1332 about user actions on
and/or off the social networking system 1330. The action logger
1340 populates the activity log 1342 with information about user
actions, enabling the social networking system 1330 to discover
various actions taken by its users within the social networking
system 1330 and outside of the social networking system 1330. Any
action that a particular user takes with respect to another node on
the social networking system 1330 may be associated with each
user's account, through information maintained in the activity log
1342 or in a similar database or other data repository. Examples of
actions taken by a user within the social networking system 1330
that are identified and stored may include, for example, adding a
connection to another user, sending a message to another user,
reading a message from another user, viewing content associated
with another user, attending an event posted by another user,
posting an image, attempting to post an image, or other actions
interacting with another user or another object. When a user takes
an action within the social networking system 1330, the action is
recorded in the activity log 1342. In one embodiment, the social
networking system 1330 maintains the activity log 1342 as a
database of entries. When an action is taken within the social
networking system 1330, an entry for the action is added to the
activity log 1342. The activity log 1342 may be referred to as an
action log.
[0126] Additionally, user actions may be associated with concepts
and actions that occur within an entity outside of the social
networking system 1330, such as an external system 1320 that is
separate from the social networking system 1330. For example, the
action logger 1340 may receive data describing a user's interaction
with an external system 1320 from the web server 1332. In this
example, the external system 1320 reports a user's interaction
according to structured actions and objects in the social
graph.
[0127] Other examples of actions where a user interacts with an
external system 1320 include a user expressing an interest in an
external system 1320 or another entity, a user posting a comment to
the social networking system 1330 that discusses an external system
1320 or a web page 1322a within the external system 1320, a user
posting to the social networking system 1330 a Uniform Resource
Locator (URL) or other identifier associated with an external
system 1320, a user attending an event associated with an external
system 1320, or any other action by a user that is related to an
external system 1320. Thus, the activity log 1342 may include
actions describing interactions between a user of the social
networking system 1330 and an external system 1320 that is separate
from the social networking system 1330.
[0128] The authorization server 1344 enforces one or more privacy
settings of the users of the social networking system 1330. A
privacy setting of a user determines how particular information
associated with a user can be shared. The privacy setting comprises
the specification of particular information associated with a user
and the specification of the entity or entities with whom the
information can be shared. Examples of entities with which
information can be shared may include other users, applications,
external systems 1320, or any entity that can potentially access
the information. The information that can be shared by a user
comprises user account information, such as profile photos, phone
numbers associated with the user, user's connections, actions taken
by the user such as adding a connection, changing user profile
information, and the like.
[0129] The privacy setting specification may be provided at
different levels of granularity. For example, the privacy setting
may identify specific information to be shared with other users;
the privacy setting identifies a work phone number or a specific
set of related information, such as, personal information including
profile photo, home phone number, and status. Alternatively, the
privacy setting may apply to all the information associated with
the user. The specification of the set of entities that can access
particular information can also be specified at various levels of
granularity. Various sets of entities with which information can be
shared may include, for example, all friends of the user, all
friends of friends, all applications, or all external systems 1320.
One embodiment allows the specification of the set of entities to
comprise an enumeration of entities. For example, the user may
provide a list of external systems 1320 that are allowed to access
certain information. Another embodiment allows the specification to
comprise a set of entities along with exceptions that are not
allowed to access the information. For example, a user may allow
all external systems 1320 to access the user's work information,
but specify a list of external systems 1320 that are not allowed to
access the work information. Certain embodiments call the list of
exceptions that are not allowed to access certain information a
"block list". External systems 1320 belonging to a block list
specified by a user are blocked from accessing the information
specified in the privacy setting. Various combinations of
granularity of specification of information, and granularity of
specification of entities, with which information is shared are
possible. For example, all personal information may be shared with
friends whereas all work information may be shared with friends of
friends.
[0130] The authorization server 1344 contains logic to determine if
certain information associated with a user can be accessed by a
user's friends, external systems 1320, and/or other applications
and entities. The external system 1320 may need authorization from
the authorization server 1344 to access the user's more private and
sensitive information, such as the user's work phone number. Based
on the user's privacy settings, the authorization server 1344
determines if another user, the external system 1320, an
application, or another entity is allowed to access information
associated with the user, including information about actions taken
by the user.
[0131] In some embodiments, the social networking system 1330 can
include a content provider module 1346. The content provider module
1346 can, for example, be implemented as the content provider
module 102 of FIG. 1. As discussed previously, it should be
appreciated that there can be many variations or other
possibilities.
Hardware Implementation
[0132] The foregoing processes and features can be implemented by a
wide variety of machine and computer system architectures and in a
wide variety of network and computing environments. FIG. 14
illustrates an example of a computer system 1400 that may be used
to implement one or more of the embodiments described herein in
accordance with an embodiment of the invention. The computer system
1400 includes sets of instructions for causing the computer system
1400 to perform the processes and features discussed herein. The
computer system 1400 may be connected (e.g., networked) to other
machines. In a networked deployment, the computer system 1400 may
operate in the capacity of a server machine or a client machine in
a client-server network environment, or as a peer machine in a
peer-to-peer (or distributed) network environment. In an embodiment
of the invention, the computer system 1400 may be the social
networking system 1330, the user device 1310, and the external
system 1420, or a component thereof. In an embodiment of the
invention, the computer system 1400 may be one server among many
that constitutes all or part of the social networking system
1330.
[0133] The computer system 1400 includes a processor 1402, a cache
1404, and one or more executable modules and drivers, stored on a
computer-readable medium, directed to the processes and features
described herein. Additionally, the computer system 1400 includes a
high performance input/output (I/O) bus 1406 and a standard I/O bus
1408. A host bridge 1410 couples processor 1402 to high performance
I/O bus 1406, whereas I/O bus bridge 1412 couples the two buses
1406 and 1408 to each other. A system memory 1414 and one or more
network interfaces 1416 couple to high performance I/O bus 1406.
The computer system 1400 may further include video memory and a
display device coupled to the video memory (not shown). Mass
storage 1418 and I/O ports 1420 couple to the standard I/O bus
1408. The computer system 1400 may optionally include a keyboard
and pointing device, a display device, or other input/output
devices (not shown) coupled to the standard I/O bus 1408.
Collectively, these elements are intended to represent a broad
category of computer hardware systems, including but not limited to
computer systems based on the x86-compatible processors
manufactured by Intel Corporation of Santa Clara, Calif., and the
x86-compatible processors manufactured by Advanced Micro Devices
(AMD), Inc., of Sunnyvale, Calif., as well as any other suitable
processor.
[0134] An operating system manages and controls the operation of
the computer system 1400, including the input and output of data to
and from software applications (not shown). The operating system
provides an interface between the software applications being
executed on the system and the hardware components of the system.
Any suitable operating system may be used, such as the LINUX
Operating System, the Apple Macintosh Operating System, available
from Apple Computer Inc. of Cupertino, Calif., UNIX operating
systems, Microsoft.RTM. Windows.RTM. operating systems, BSD
operating systems, and the like. Other implementations are
possible.
[0135] The elements of the computer system 1400 are described in
greater detail below. In particular, the network interface 1416
provides communication between the computer system 1400 and any of
a wide range of networks, such as an Ethernet (e.g., IEEE 802.3)
network, a backplane, etc. The mass storage 1418 provides permanent
storage for the data and programming instructions to perform the
above-described processes and features implemented by the
respective computing systems identified above, whereas the system
memory 1414 (e.g., DRAM) provides temporary storage for the data
and programming instructions when executed by the processor 1402.
The I/O ports 1420 may be one or more serial and/or parallel
communication ports that provide communication between additional
peripheral devices, which may be coupled to the computer system
1400.
[0136] The computer system 1400 may include a variety of system
architectures, and various components of the computer system 1400
may be rearranged. For example, the cache 1404 may be on-chip with
processor 1402. Alternatively, the cache 1404 and the processor
1402 may be packed together as a "processor module", with processor
1402 being referred to as the "processor core". Furthermore,
certain embodiments of the invention may neither require nor
include all of the above components. For example, peripheral
devices coupled to the standard I/O bus 1408 may couple to the high
performance I/O bus 1406. In addition, in some embodiments, only a
single bus may exist, with the components of the computer system
1400 being coupled to the single bus. Moreover, the computer system
1400 may include additional components, such as additional
processors, storage devices, or memories.
[0137] In general, the processes and features described herein may
be implemented as part of an operating system or a specific
application, component, program, object, module, or series of
instructions referred to as "programs". For example, one or more
programs may be used to execute specific processes described
herein. The programs typically comprise one or more instructions in
various memory and storage devices in the computer system 1400
that, when read and executed by one or more processors, cause the
computer system 1400 to perform operations to execute the processes
and features described herein. The processes and features described
herein may be implemented in software, firmware, hardware (e.g., an
application specific integrated circuit), or any combination
thereof.
[0138] In one implementation, the processes and features described
herein are implemented as a series of executable modules run by the
computer system 1400, individually or collectively in a distributed
computing environment. The foregoing modules may be realized by
hardware, executable modules stored on a computer-readable medium
(or machine-readable medium), or a combination of both. For
example, the modules may comprise a plurality or series of
instructions to be executed by a processor in a hardware system,
such as the processor 1402. Initially, the series of instructions
may be stored on a storage device, such as the mass storage 1418.
However, the series of instructions can be stored on any suitable
computer readable storage medium. Furthermore, the series of
instructions need not be stored locally, and could be received from
a remote storage device, such as a server on a network, via the
network interface 1416. The instructions are copied from the
storage device, such as the mass storage 1418, into the system
memory 1414 and then accessed and executed by the processor 1402.
In various implementations, a module or modules can be executed by
a processor or multiple processors in one or multiple locations,
such as multiple servers in a parallel processing environment.
[0139] Examples of computer-readable media include, but are not
limited to, recordable type media such as volatile and non-volatile
memory devices; solid state memories; floppy and other removable
disks; hard disk drives; magnetic media; optical disks (e.g.,
Compact Disk Read-Only Memory (CD ROMS), Digital Versatile Disks
(DVDs)); other similar non-transitory (or transitory), tangible (or
non-tangible) storage medium; or any type of medium suitable for
storing, encoding, or carrying a series of instructions for
execution by the computer system 1400 to perform any one or more of
the processes and features described herein.
[0140] For purposes of explanation, numerous specific details are
set forth in order to provide a thorough understanding of the
description. It will be apparent, however, to one skilled in the
art that embodiments of the disclosure can be practiced without
these specific details. In some instances, modules, structures,
processes, features, and devices are shown in block diagram form in
order to avoid obscuring the description. In other instances,
functional block diagrams and flow diagrams are shown to represent
data and logic flows. The components of block diagrams and flow
diagrams (e.g., modules, blocks, structures, devices, features,
etc.) may be variously combined, separated, removed, reordered, and
replaced in a manner other than as expressly described and depicted
herein.
[0141] Reference in this specification to "one embodiment", "an
embodiment", "other embodiments", "one series of embodiments",
"some embodiments", "various embodiments", or the like means that a
particular feature, design, structure, or characteristic described
in connection with the embodiment is included in at least one
embodiment of the disclosure. The appearances of, for example, the
phrase "in one embodiment" or "in an embodiment" in various places
in the specification are not necessarily all referring to the same
embodiment, nor are separate or alternative embodiments mutually
exclusive of other embodiments. Moreover, whether or not there is
express reference to an "embodiment" or the like, various features
are described, which may be variously combined and included in some
embodiments, but also variously omitted in other embodiments.
Similarly, various features are described that may be preferences
or requirements for some embodiments, but not other
embodiments.
[0142] The language used herein has been principally selected for
readability and instructional purposes, and it may not have been
selected to delineate or circumscribe the inventive subject matter.
It is therefore intended that the scope of the invention be limited
not by this detailed description, but rather by any claims that
issue on an application based hereon. Accordingly, the disclosure
of the embodiments of the invention is intended to be illustrative,
but not limiting, of the scope of the invention, which is set forth
in the following claims.
* * * * *