U.S. patent application number 15/827122 was filed with the patent office on 2018-03-22 for search query classification.
The applicant listed for this patent is Amazon Technologies, Inc.. Invention is credited to Gaurav Chanda.
Application Number | 20180081882 15/827122 |
Document ID | / |
Family ID | 60812838 |
Filed Date | 2018-03-22 |
United States Patent
Application |
20180081882 |
Kind Code |
A1 |
Chanda; Gaurav |
March 22, 2018 |
SEARCH QUERY CLASSIFICATION
Abstract
Disclosed are various embodiments for classifying search
queries. A computing device identifies a user account associated
with a submission of a search query to an electronic commerce
application. The computing device then identifies a network page
provided by the electronic commerce application, wherein the
network page is requested with the user account. Subsequently, the
computing device classifies the search query based at least in part
on the requested network page.
Inventors: |
Chanda; Gaurav; (Seattle,
WA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Amazon Technologies, Inc. |
Seattle |
WA |
US |
|
|
Family ID: |
60812838 |
Appl. No.: |
15/827122 |
Filed: |
November 30, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14629570 |
Feb 24, 2015 |
9864784 |
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15827122 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 16/24578 20190101;
G06F 16/951 20190101 |
International
Class: |
G06F 17/30 20060101
G06F017/30 |
Claims
1. A system, comprising: a computing device comprising a processor
and a memory; and an application comprising machine readable
instructions stored in the memory that, when executed by the
processor, cause the computing device to at least: determine a
classification of a search query submitted to the computing device,
wherein the classification of the search query is based at least in
part on a probability that a type of network page will be requested
subsequent to a submission of the search query; and generate a
network page in response to a submission of the search query,
wherein at least a portion of the content of the network page is
based at least in part on the classification of the submitted
search query.
2. The system of claim 1, wherein the machine readable instructions
that cause the computing device to generate the network page in
response to the submission of the search query further comprise
machine readable instructions that cause the computing device to at
least: identify content associated with classification of the
search query; and incorporate the content associated with the
classification of the search query into the network page.
3. The method of claim 2, wherein the content associated with the
classification of the search query comprises a recommended network
page.
4. The system of claim 3, wherein the recommended network page has
a higher probability of being requested after submission of the
search query in comparison to a probability that an unrecommended
network page will be requested after submission of the search
query.
5. The system of claim 1, wherein the machine readable instructions
that cause the computing device to determine the classification of
the search query further comprise machine readable instructions
that, when executed by the computing device, cause the computing
device to at least: match the search query to at least one of a
plurality of previously classified search queries; and identify the
classification that matches the at least one of the plurality of
previously classified search queries.
6. The system of claim 1, wherein the network page comprises a
first network page and wherein the search query is submitted to the
computing device via a search bar within a second network page.
7. The system of claim 1, wherein the classification of the search
query comprises at least one of a non-product search query or a
product search query.
8. The system of claim 1, wherein the machine readable
instructions, when executed by the processor, further cause the
computing device to at least calculate a ratio of an expected
number of requests for the type of network page compared to an
observed number of requests for the type of network page occurring
after the submission of the search query.
9. The system of claim 8, wherein the probability that the type of
network page that will be requested subsequent to the submission of
the search query is based at least in part on the ratio of the
expected number of requests for the type of network page compared
to the observed number of requests for the type of network page
occurring after the submission of the search query.
10. A method, comprising: determining, via a computing device, a
classification of a search query submitted to the computing device,
wherein the classification of the search query is based at least in
part on a probability that a type of network page will be requested
subsequent to a submission of the search query; and generating, via
the computing device, a network page in response to a submission of
the search query, wherein at least a portion of the content of the
network page is based at least in part on the classification of the
submitted search query.
11. The method of claim Error! Bookmark not defined.0, wherein
generating the network page in response to the submission of the
search query further comprises: identifying, via the computing
device, content associated with classification of the search query;
and incorporating, via the computing device, the content associated
with the classification of the search query into the network
page.
12. The method of claim 11, wherein the content associated with the
classification of the search query comprises a recommended network
page.
13. The method of claim 12, wherein the recommended network page
has a higher probability of being requested after submission of the
search query in comparison to a probability that an unrecommended
network page will be requested after submission of the search
query.
14. The method of claim 10, wherein determining the classification
of the search query further comprises: matching, via the computing
device, the search query to at least one of a plurality of
previously classified search queries; and identifying, via the
computing device, the classification that matches the at least one
of the plurality of previously classified search queries.
15. The method of claim 10, wherein the network page comprises a
first network page and wherein the search query is submitted to the
computing device via a search bar within a second network page.
16. The method of claim 10, wherein the classification of the
search query comprises at least one of a non-product search query
or a product search query.
17. The method of claim 10, wherein the probability that the type
of network page that will be requested subsequent to the submission
of the search query is determined at least in part by calculating,
via the computing device, a ratio of an expected number of requests
for the type of network page compared to an observed number of
requests for the type of network page occurring after the
submission of the search query.
18. A system, comprising: a computing device comprising a processor
and a memory; and an application comprising machine readable
instructions stored in the memory that, when executed by the
processor, cause the computing device to at least: match a search
query to at least one of a plurality of previously classified
search queries; identify a classification that matches the at least
one of the plurality of previously classified search queries;
assign to the search query the classification that matches the at
least one of the plurality of previously classified search queries;
identify content associated with classification; generate a network
page in response to a submission of the search query, wherein at
least a portion of the content of the network page is based at
least in part on the classification; and incorporate the content
associated with the classification of the search query into the
network page.
19. The system of claim 18, wherein the content associated with the
classification of the search query comprises a recommended network
page.
20. The system of claim 18, wherein the recommended network page
has a higher probability of being requested after submission of the
search query in comparison to a probability that an unrecommended
network page will be requested after submission of the search
query.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority to, and the benefit of,
copending U.S. patent application Ser. No. 14/629,570, filed on
Feb. 24, 2015, and entitled "SEARCH QUERY CLASSIFICATION," which is
incorporated by reference as if set forth herein in its
entirety.
BACKGROUND
[0002] Electronic commerce systems may provide search functionality
for users to search for products or items available for sale from
an electronic catalog of the electronic commerce system. This
search functionality may, for example, allow for users to submit
search queries. Users may also be able to further sort or otherwise
refine the search results that are returned.
BRIEF DESCRIPTION OF THE DRAWINGS
[0003] Many aspects of the present disclosure can be better
understood with reference to the following drawings. The components
in the drawings are not necessarily to scale, with emphasis instead
being placed upon clearly illustrating the principles of the
disclosure. Moreover, in the drawings, like reference numerals
designate corresponding parts throughout the several views.
[0004] FIG. 1 is an illustration of one of several embodiments of
the present disclosure.
[0005] FIG. 2 is a drawing of a networked environment according to
various embodiments of the present disclosure.
[0006] FIG. 3 is a flowchart illustrating one example of
functionality implemented as portions of an application executed in
a computing environment in the networked environment of FIG. 2
according to various embodiments of the present disclosure.
[0007] FIG. 4 is a flowchart illustrating one example of
functionality implemented as portions of an application executed in
a computing environment in the networked environment of FIG. 2
according to various embodiments of the present disclosure.
[0008] FIG. 5 is a schematic block diagram that provides one
example illustration of a computing environment employed in the
networked environment of FIG. 1 according to various embodiments of
the present disclosure.
DETAILED DESCRIPTION
[0009] Disclosed are various embodiments for classifying search
queries. Network pages, such as web pages provided by electronic
commerce applications, may provide a search bar, field, or similar
user interface element to assist in searching for items in a
product catalog. Search queries entered in the search bar may cause
a list of matching products or items to be returned by the
electronic commerce application. However, users may also wish to
find network pages of the electronic commerce application that are
unrelated to products, such as a help or customer service network
page, a network page with company contact information, a network
page for managing a user account, and/or similar non-product
related network pages. In such instances, users may submit a search
query via the search bar to find the non-product related network
page for which the user is searching.
[0010] In order to provide accurate search results, search queries
may be classified as product search queries, non-product search
queries, help search queries, and/or classified as other types of
search queries. The search results provided in response to the
search query may be based at least in part on the type or
classification of the submitted search query. In the following
discussion, a general description of the system and its components
is provided, followed by a discussion of the operation of the
same.
[0011] Beginning with FIG. 1, shown is a user interface 100, such
as a browser window or other interface. Within the user interface
100 are displayed a number of search results 103 rendered in
response to submission of a search query. Also depicted in the user
interface 100 is a suggested search result 106. The suggested
search result 106 may be included in the response to a search query
if the search query has been determined to be a search query
associated with attempts to find specific content, such as the help
section of a network site, instead of a generic search query or a
default search query, such as a product search query submitted to
an electronic commerce application.
[0012] As illustrated, a search query of "user help" has been
previously submitted. The submitted search query, in some
embodiments, may be depicted in an address bar 109, as shown. In
response, a number of search results 103 for products or items
available for purchase that match the search query "user help" have
been returned. However, search query "user help" may have been
previously classified as a non-product search query, such as a help
search query. Therefore, a suggested search result 106 directing a
user to the user help section of the electronic commerce
application is included with the search results 103 in case the
user was looking for the user help section of the electronic
commerce application instead of search of products that matched the
search query "user help."
[0013] With reference to FIG. 2, shown is a networked environment
200 according to various embodiments. The networked environment 200
includes a computing environment 203 and a client device 206, which
are in data communication with each other via a network 209. The
network 209 includes, for example, the Internet, intranets,
extranets, wide area networks (WANs), local area networks (LANs),
wired networks, wireless networks, or other suitable networks,
etc., or any combination of two or more such networks. For example,
such networks may comprise satellite networks, cable networks,
Ethernet networks, and other types of networks.
[0014] The computing environment 203 may comprise, for example, a
server computer or any other system providing computing capability.
Alternatively, the computing environment 203 may employ a plurality
of computing devices that may be arranged, for example, in one or
more server banks or computer banks or other arrangements. Such
computing devices may be located in a single installation or may be
distributed among many different geographical locations. For
example, the computing environment 203 may include a plurality of
computing devices that together may comprise a hosted computing
resource, a grid computing resource, and/or any other distributed
computing arrangement. In some cases, the computing environment 203
may correspond to an elastic computing resource where the allotted
capacity of processing, network, storage, or other
computing-related resources may vary over time.
[0015] Various applications and/or other functionality may be
executed in the computing environment 203 according to various
embodiments. Also, various data is stored in a data store 213 that
is accessible to the computing environment 203. The data store 213
may be representative of a plurality of data stores 213 as can be
appreciated. The data stored in the data store 213, for example, is
associated with the operation of the various applications and/or
functional entities described below.
[0016] The components executed on the computing environment 203,
for example, include an electronic commerce application 216, a
query classification application 219, a network page server
application 223, and other applications, services, processes,
systems, engines, or functionality not discussed in detail herein.
The electronic commerce application 216 is executed in order to
facilitate online purchases of items over the network 209. The
electronic commerce application 216 may generate network pages,
such as web pages, that provide descriptions of items and allow for
purchase of the item. The electronic commerce application 216 may
also provide search functionality, such as a tool bar, text input
field, filters, and/or other user interface elements, that
facilitate searching a product catalog for one or more items. The
electronic commerce application 216 may also perform various
backend functions associated with the online presence of a merchant
in order to facilitate the online purchase of items as will be
described. The query classification 219 is executed to classify
search queries received from client devices 206, as will be further
described herein. The network page server application 223 is
executed to dynamically generate network pages on behalf of the
electronic commerce application 216, as will be further described
herein.
[0017] The data stored in the data store 213 includes, for example,
classified search queries 226, user accounts 229, network page
templates 233, a product catalog 236, and potentially other data.
The individual ones of the classified search queries 226 may
correspond to one or more search query categories 239 and one or
more suggested network pages 243. A user account 229 may include
one or more requested network pages 246 requested with the user
account 229 and a submitted search query 249 submitted to the
electronic commerce application 216 with the user account 229. The
product catalog may include one or more items 253 for sale through
the electronic commerce application 216.
[0018] The classified search queries 226 represent the set of
search queries that have been previously submitted to the
electronic commerce application 216 and have been classified by the
query classification application 219 as belonging to one or more
search query categories 239. Each classified search query 226 may
be associated with one or more search query categories 239 and with
a suggested network page 243.
[0019] Search query categories 239 represent a type,
classification, or other taxonomy for search queries. Examples of
search query categories 239 may include product search queries,
which may represent search queries associated with searches of the
product catalog 236, and non-product search queries, which may
represent search queries for information not contained in the
product catalog 236. Non-product search queries may, for example,
include searches for customer service information, user account
management information, company contact information, and help with
using various aspects of the electronic commerce application 216 in
general. In some embodiments, a classified search query 226 may be
assigned to multiple search query categories 239.
[0020] A suggested network page 243 represents a network page or an
address for a network page that is likely to be the intended
destination of a user of the electronic commerce application 216.
For example, a user submitting a non-product search query may
intend to find the help page of the electronic commerce application
216 and not network pages of products that match the search term
"help." Therefore, the suggested network page 243 for the
non-product search query may represent the help page of the
electronic commerce application 216. In various embodiments, a
classified search query 226 may include multiple suggested network
pages 243.
[0021] The user accounts 229 may include data or attributes
associated with the account of a user of the electronic commerce
application 216. Such data or attributes may include, for example,
the name, address, phone number, email address, employer,
occupation or profession, purchase or order history, demographic
data, or other data of the user. Such data or attributes may also
include authorization data such as user name, password, personal
identification number (PIN), or other similar data. User accounts
229 may also include data for tracking interactions of a user with
the electronic commerce application 216, such as any requested
network pages 246 and/or a submitted search query 249.
[0022] A requested network page 246 represents a request for a
network page submitted to the electronic commerce application 216
with the user account 229. This may include the address of the
requested network page 246, as represented by a uniform resource
locator (URL) or other identifier. This may also include the time
that the request was made and data regarding how the requested
network page 246 was reached. For example, this may include data
indicating that the requested network page 246 was reached from a
link located on a previously visited network page, such as a search
results page, and the address of the previously visited network
page, as represented by a URL for the previously visited network
page.
[0023] A submitted search query 249 represents a search query
submitted to the electronic commerce application 216 with the user
account 229. This may include the text of the submitted search
query 249, the time that the submitted search query 249 was
received by the electronic commerce application 216, the time that
the submitted search query 249 was sent from a client device 206,
and/or potentially other data.
[0024] A network page template 233 represents data specifying the
layout and content of a network page generated by the network page
server application 223. A network page template 223 may, for
example, specify where information for individual items 253 is to
be placed in a network page generated by the network page server
application 223 or where search results generated by the electronic
commerce application 216 are to be located in the network page
generated by the network page server application 223. The network
page template 223 may also specify a theme, style, color scheme,
font, and/or details of the network page generated by the network
page server application 223.
[0025] A product catalog 236 represents a schema, taxonomy,
directory, or other organizational scheme for items 253 available
for purchase via the electronic commerce application 216. Items 253
may include goods, services, digital or electronic media, and
similar products or merchandise available for purchases through the
electronic commerce application 216. Each item 253 has a unique
identifier 256 which uniquely identifies the item 253 from other
items 253 listed in the product catalog 236. The unique identifier
256 may be a catalog or index number, a Universal Product Code
("UPC") number, or similar uniquely identifying code, number,
symbol, or attribute.
[0026] The client device 206 is representative of a plurality of
client devices that may be coupled to the network 209. The client
device 206 may comprise, for example, a processor-based system such
as a computer system. Such a computer system may be embodied in the
form of a desktop computer, a laptop computer, personal digital
assistants, cellular telephones, smartphones, set-top boxes, music
players, web pads, tablet computer systems, game consoles,
electronic book readers, or other devices with like capability. The
client device 206 may include a display 259. The display 259 may
comprise, for example, one or more devices such as liquid crystal
display (LCD) displays, gas plasma-based flat panel displays,
organic light emitting diode (OLED) displays, electrophoretic ink
(E ink) displays, LCD projectors, or other types of display
devices, etc.
[0027] The client device 206 may be configured to execute various
applications such as a client application 263 and/or other
applications. The client application 263 may be executed in a
client device 206, for example, to access network content served up
by the computing environment 203 and/or other servers, thereby
rendering a user interface 100 on the display 259. To this end, the
client application 263 may comprise, for example, a browser, a
dedicated application, etc., and the user interface 100 may
comprise a network page, an application screen, etc. The client
device 206 may be configured to execute applications beyond the
client application 263 such as, for example, email applications,
social networking applications, word processors, spreadsheets,
and/or other applications.
[0028] Next, a general description of the operation of the various
components of the networked environment 200 is provided. To begin,
one or more search queries and one or more requests for network
pages are received by the electronic commerce application 216 from
a client application 263 associated with a user account 229. Each
search query received is stored by the electronic commerce
application 216 as a submitted search query 249 of the user account
229 and each request for a network page is stored by the electronic
commerce application 216 as a requested network page 246 of the
user account 229.
[0029] For each submitted search query 249, the electronic commerce
application 216 compares the submitted search query 249 with each
of the classified search queries 226 to determine whether the
submitted search query 249 matches one of the classified search
queries 226. If the submitted search query 249 matches one of the
classified search queries 226, then the electronic commerce
application 216 retrieves the search query categories 239 and
suggested network pages 243 of the matching classified search query
226 and supplies them to the network page server application 223.
The network page server application 223 then uses the search query
categories 239 and the suggested network pages 243 to select an
appropriate network page template 233. The network page server
application 223 then generates and returns a network page to the
client application 263.
[0030] However, if the submitted search query 249 does not match a
classified search query 226, then the electronic commerce
application 216 searches the product catalog 236 for one or more
items 253 that match one or more terms in the submitted search
query 249. The electronic commerce application 216 supplies the
list of matching items 253 to the network page server application
223, which generates a network page that includes information about
the items 253 in the manner specified by another network page
template 233.
[0031] Concurrent with the process described above, the query
classification application 219 analyzes the submitted search query
249 for classification. The query classification application 219
may, for example, track the number of times that the electronic
commerce application 216 has received the submitted search query
249, either from a single user account 229 or from multiple user
accounts 229. The query classification application 219 may also
track, for example, the number of times that users have navigated
to a particular requested network page 246 after the electronic
commerce application 216 has received the submitted search query
249. If users have navigated to a particular requested network page
246 after the electronic commerce application 216 has received the
submitted search query 249 more often than expected, then the
electronic commerce application 216 may add the submitted search
query 249 to the set of classified search queries 226 by setting
the suggested network page 243 to the particular requested network
page 246 that is visited more frequently than expected and by
assigning a search query category 239 based upon the type of the
particular requested network page 246 that has been visited more
often than expected.
[0032] For example, a user may submit a search query of "user
help." The user may then be presented with a network page
containing a listing of items 253 that match one or more of the
search terms in the "user help" query. However, if a user is more
interested in finding the help section provided by the electronic
commerce application 216, such as a help page, the user may then
search for and follow a link to the help page instead of following
a link to a network page for one of the items 253. If a greater
than expected or predicted number of users follow the link to the
help page after submitting the query "user help," then the query
classification application 219 may determine that the query "user
help" is not a product search query, but is a non-product search
query, such as a query intended to lead a user to the help page.
The query classification application 219 may subsequently include
the search query in the list of classified search queries 226 and
set the values for the search query category 239 and the suggested
network page 243 accordingly.
[0033] Moving next to FIG. 3, shown is a flowchart that provides
one example of the operation of a portion of the query
classification application 219 according to various embodiments. It
is understood that the flowchart of FIG. 3 provides merely an
example of the many different types of functional arrangements that
may be employed to implement the operation of the portion of the
query classification application 219 as described herein. As an
alternative, the flowchart of FIG. 3 may be viewed as depicting an
example of elements of a method implemented in the computing
environment 203 (FIG. 2) according to one or more embodiments.
[0034] Beginning with box 303, the query classification application
219 identifies a user account 229 (FIG. 2) associated with a
submitted search query 249 (FIG. 2) received from a client
application 263 (FIG. 2), such as a browser or other application.
The query classification application 219 may identify the user
account 229, for example, by checking for a cookie, session
identifier, or similar identification token included with the
submitted search query 249. If a user is not logged in, however,
the user account 229 may be identified through other means, such as
by internet protocol (IP) address or a browser fingerprint based
upon a unique combination of browser plugins, system fonts,
HTTP_ACCEPT headers, user agent, and other information reported by
the browser executing on the client device 206 (FIG. 2) of the
user. By identifying a user account 229 to associate with a
submitted search query 249, the search behavior of individual users
may be tracked so that the submitted search query may be accurately
classified, as will be discussed in further detail herein.
[0035] Moving on to box 306, the query classification application
219 identifies a requested network page 246 (FIG. 2) associated
with the user account 229. The requested network page 246 may be
identified, for example, by analyzing requests for network pages
sent to the electronic commerce application and/or network page
server application 223 (FIG. 2). In some embodiments, the query
classification application 219 may limit itself to identifying only
requested network pages 246 that were requested after the submitted
search query 249 was received. Such behavior may indicate that a
user is actively searching for the requested network page 246 by
using the submitted search query 249.
[0036] Referring next to box 307, the query classification
application 219 may determine whether the requested network page
246 is a ranked higher than a predefined threshold. For any
submitted search query 249, links to a number of network pages may
provided in response. These links to network pages may be sorted
and ranked, for example, according to relevancy, popularity, or
some other metric, where links to more relevant or popular network
pages are provided first. By determining whether a requested
network page 246 is ranked prior to classifying the submitted
search query 249 improper or incorrect classifications of the
submitted search query 249 may be minimized. If the requested
network page 246 is ranked higher than the threshold, then
execution proceeds to box 309. Otherwise, the previously described
path of execution subsequently ends.
[0037] Proceeding next to box 309, the query classification
application 219 associates the submitted search query 249 with the
requested network page 246, strengthening the correlation between
the submitted search query 249 and the requested network page 246.
For example, the query classification application 219 may store a
correlation between the submitted search query 249 and the
requested network page 246 if the requested network page 246 is the
first network page requested after the submitted search query 249
is received by the electronic commerce application 216. In some
embodiments, the query classification application 219 may store a
correlation between the submitted search query 249 and the
requested network page 246 if the requested network page 246 is one
of several network pages requested after the submitted search query
249 is received by the electronic commerce application 216. For
example, the query classification application 219 may identify a
correlation between one of the first two, three, four, five, or
other threshold number of network pages requested after the
submitted search query 249 is received by the electronic commerce
application 216 and the submitted search query 249 itself. In other
embodiments, the query classification application 219 may store a
correlation between the submitted search query 249 and the
requested network page 246 if the requested network page 246 is
requested within a predefined period of time after the submitted
search query 249 is received by the electronic commerce application
216.
[0038] Referring next to box 313, the query classification
application 219 calculates the probability that the submitted
search query 249 would lead the user to the requested network page
246 in comparison to other network pages. This probability may be
represented, for example by the equation:
P=P(B|A)-P(B) (1)
where P(B|A) represents the observed probability that a user
followed submitted search query 249 "A" to requested network page
246 "B" in comparison to those users arrived at requested network
page 246 "B" independently. The resulting value "P" represents the
association between the submitted search query 249 and the
requested network page 246. Larger values of "P" may indicate that
the submitted search query 249 is received from users who are
actively searching for the requested network page 246. Other
models, which may be used in various embodiments of the present
disclosure, are disclosed in U.S. Pat. No. 8,239,287, entitled
"System for Detecting Probabilistic Associations Between Items,"
granted Aug. 7, 2012, which is incorporated by reference in its
entirety as if set forth fully herein.
[0039] Moving on to box 316, the query classification application
219 determines whether the calculated probability "P," as described
in equation 1, exceeds a previously defined threshold value. The
previously defined threshold value may be set based on empirical
observations of user behavior. Generally, the threshold value will
be one that is high enough that misclassifications will be avoided
or minimized, but not so high as to cause valid classifications to
be overlooked. If the calculated probability exceeds the previously
defined threshold, then the previously described path of execution
proceeds to box 319. Otherwise, the previously described path of
execution subsequently ends.
[0040] Proceeding to box 319, the query classification application
219 assigns a search query category 239 to the submitted search
query 249 and stores the requested network page 246 as a suggested
network page 243 for the newly classified search query 226. The
search query category 239 may be based at least in part on the
requested network page 246. For example, if the requested network
page 246 is for a particular portion or functionality of the
electronic commerce application 216, such as a help section, an
account management section, or other portion of the electronic
commerce application 216, then a corresponding search query
category 239, such as "help query," "account query," or a more
general "non-product query" search query category 239 may be
selected. The previously described path of execution subsequently
ends.
[0041] Turning now to FIG. 4, shown is a flowchart that provides
one example of the operation of a portion of the network page
server application 223 according to various embodiments. It is
understood that the flowchart of FIG. 4 provides merely an example
of the many different types of functional arrangements that may be
employed to implement the operation of the portion of the network
page server application 223 as described herein. As an alternative,
the flowchart of FIG. 4 may be viewed as depicting an example of
elements of a method implemented in the computing environment 203
(FIG. 2) according to one or more embodiments.
[0042] Beginning with box 403, network page server application 223
determines the classification of the search query category 239
(FIG. 2) of a submitted search query 249 (FIG. 2). The network page
server application 223 may, for example, compare the submitted
search query 249 with a list of classified search queries 226 (FIG.
2). If the submitted search query 249 matches one of the classified
search queries 226, then the network page server application 223
uses the search query category 239 of the matching classified
search query 226. If the submitted search query 249 does not match
any of the classified search queries 226, then the network page
server application 223 may use a default search query category 239.
For example, in some embodiments, the default search query category
239 may correspond to a "product search query" or similar query
type indicating that submitted search query 249 is a search query
for items 253 (FIG. 2) in the product catalog 236 (FIG. 2).
[0043] Moving on to box 406, the network page server application
223 identifies content for network page responsive to the submitted
search query 249. The content may be specified, for example, by a
network page template 233 used to generate network pages. For
example, the network page server application 223 may identify a
network page template 233 based on the search query category 239 as
previously determined. In other embodiments, the network page
template 233 may specify that certain content be included in the
generated network page based upon the search query category 239, as
previously determined. In other embodiments, the network page
server application 223 may use the suggested network page 243 for
the response to the submitted search query 249 instead of
generating a responsive network page according to the
specifications of a network page template 233.
[0044] Proceeding next to box 409, the network page server
application 223 generates a network page. In some embodiments, the
network page server application 223 may simply use the suggested
network page 243 associated with the search query category 239 as
previously determined. In other embodiments, the network page
server application 223 may dynamically generate a network page in
the manner specified by the network page template 233.
[0045] Referring next to box 413, the network page server
application 223 sends the generated network page to the client
application 206. The network page may be sent, for example, using a
version of the hypertext transfer protocol (HTTP) or similar data
transfer protocol. The previously described path of execution
subsequently ends.
[0046] With reference to FIG. 5, shown is a schematic block diagram
of the computing environment 203 according to an embodiment of the
present disclosure. The computing environment 203 includes one or
more computing devices 500. Each computing device 500 includes at
least one processor circuit, for example, having a processor 503
and a memory 506, both of which are coupled to a local interface
509. To this end, each computing device 500 may comprise, for
example, at least one server computer or like device. The local
interface 509 may comprise, for example, a data bus with an
accompanying address/control bus or other bus structure as can be
appreciated.
[0047] Stored in the memory 506 are both data and several
components that are executable by the processor 503. In particular,
stored in the memory 506 and executable by the processor 503 are
the electronic commerce application 216, the query classification
application 219, the network page server application 223, and
potentially other applications. Also stored in the memory 506 may
be a data store 213 and other data. In addition, an operating
system may be stored in the memory 506 and executable by the
processor 503.
[0048] It is understood that there may be other applications that
are stored in the memory 506 and are executable by the processor
503 as can be appreciated. Where any component discussed herein is
implemented in the form of software, any one of a number of
programming languages may be employed such as, for example, C, C++,
C#, Objective C, Java.RTM., JavaScript.RTM., Perl, PHP, Visual
Basic.RTM., Python.RTM., Ruby, Flash.RTM., or other programming
languages.
[0049] A number of software components are stored in the memory 506
and are executable by the processor 503. In this respect, the term
"executable" means a program file that is in a form that can
ultimately be run by the processor 503. Examples of executable
programs may be, for example, a compiled program that can be
translated into machine code in a format that can be loaded into a
random access portion of the memory 506 and run by the processor
503, source code that may be expressed in proper format such as
object code that is capable of being loaded into a random access
portion of the memory 506 and executed by the processor 503, or
source code that may be interpreted by another executable program
to generate instructions in a random access portion of the memory
506 to be executed by the processor 503, etc. An executable program
may be stored in any portion or component of the memory 506
including, for example, random access memory (RAM), read-only
memory (ROM), hard drive, solid-state drive, USB flash drive,
memory card, optical disc such as compact disc (CD) or digital
versatile disc (DVD), floppy disk, magnetic tape, or other memory
components.
[0050] The memory 506 is defined herein as including both volatile
and nonvolatile memory and data storage components. Volatile
components are those that do not retain data values upon loss of
power. Nonvolatile components are those that retain data upon a
loss of power. Thus, the memory 506 may comprise, for example,
random access memory (RAM), read-only memory (ROM), hard disk
drives, solid-state drives, USB flash drives, memory cards accessed
via a memory card reader, floppy disks accessed via an associated
floppy disk drive, optical discs accessed via an optical disc
drive, magnetic tapes accessed via an appropriate tape drive,
and/or other memory components, or a combination of any two or more
of these memory components. In addition, the RAM may comprise, for
example, static random access memory (SRAM), dynamic random access
memory (DRAM), or magnetic random access memory (MRAM) and other
such devices. The ROM may comprise, for example, a programmable
read-only memory (PROM), an erasable programmable read-only memory
(EPROM), an electrically erasable programmable read-only memory
(EEPROM), or other like memory device.
[0051] Also, the processor 503 may represent multiple processors
503 and/or multiple processor cores and the memory 506 may
represent multiple memories 506 that operate in parallel processing
circuits, respectively. In such a case, the local interface 509 may
be an appropriate network that facilitates communication between
any two of the multiple processors 503, between any processor 503
and any of the memories 506, or between any two of the memories
506, etc. The local interface 509 may comprise additional systems
designed to coordinate this communication, including, for example,
performing load balancing. The processor 503 may be of electrical
or of some other available construction.
[0052] Although the electronic commerce application 216, the query
classification application 219, the network page server application
223, and other various systems described herein may be embodied in
software or code executed by general purpose hardware as discussed
above, as an alternative the same may also be embodied in dedicated
hardware or a combination of software/general purpose hardware and
dedicated hardware. If embodied in dedicated hardware, each can be
implemented as a circuit or state machine that employs any one of
or a combination of a number of technologies. These technologies
may include, but are not limited to, discrete logic circuits having
logic gates for implementing various logic functions upon an
application of one or more data signals, application specific
integrated circuits (ASICs) having appropriate logic gates,
field-programmable gate arrays (FPGAs), or other components, etc.
Such technologies are generally well known by those skilled in the
art and, consequently, are not described in detail herein.
[0053] The flowcharts of FIGS. 3 and 4 show the functionality and
operation of an implementation of portions of the query
classification application 219 and the network page server
application 223s. If embodied in software, each block may represent
a module, segment, or portion of code that comprises program
instructions to implement the specified logical function(s). The
program instructions may be embodied in the form of source code
that comprises human-readable statements written in a programming
language or machine code that comprises numerical instructions
recognizable by a suitable execution system such as a processor 503
in a computer system or other system. The machine code may be
converted from the source code, etc. If embodied in hardware, each
block may represent a circuit or a number of interconnected
circuits to implement the specified logical function(s).
[0054] Although the flowcharts of FIGS. 3 and 4 show a specific
order of execution, it is understood that the order of execution
may differ from that which is depicted. For example, the order of
execution of two or more blocks may be scrambled relative to the
order shown. Also, two or more blocks shown in succession in FIGS.
3 and 4 may be executed concurrently or with partial concurrence.
Further, in some embodiments, one or more of the blocks shown in
FIGS. 3 and 4 may be skipped or omitted. In addition, any number of
counters, state variables, warning semaphores, or messages might be
added to the logical flow described herein, for purposes of
enhanced utility, accounting, performance measurement, or providing
troubleshooting aids, etc. It is understood that all such
variations are within the scope of the present disclosure.
[0055] Also, any logic or application described herein, including
the electronic commerce application 216, the query classification
application 219, and the network page server application 223, that
comprises software or code can be embodied in any non-transitory
computer-readable medium for use by or in connection with an
instruction execution system such as, for example, a processor 503
in a computer system or other system. In this sense, the logic may
comprise, for example, statements including instructions and
declarations that can be fetched from the computer-readable medium
and executed by the instruction execution system. In the context of
the present disclosure, a "computer-readable medium" can be any
medium that can contain, store, or maintain the logic or
application described herein for use by or in connection with the
instruction execution system.
[0056] The computer-readable medium can comprise any one of many
physical media such as, for example, magnetic, optical, or
semiconductor media. More specific examples of a suitable
computer-readable medium would include, but are not limited to,
magnetic tapes, magnetic floppy diskettes, magnetic hard drives,
memory cards, solid-state drives, USB flash drives, or optical
discs. Also, the computer-readable medium may be a random access
memory (RAM) including, for example, static random access memory
(SRAM) and dynamic random access memory (DRAM), or magnetic random
access memory (MRAM). In addition, the computer-readable medium may
be a read-only memory (ROM), a programmable read-only memory
(PROM), an erasable programmable read-only memory (EPROM), an
electrically erasable programmable read-only memory (EEPROM), or
other type of memory device.
[0057] Further, any logic or application described herein,
including the electronic commerce application 216, the query
classification application 219, and the network page server
application 223, may be implemented and structured in a variety of
ways. For example, one or more applications described may be
implemented as modules or components of a single application.
Further, one or more applications described herein may be executed
in shared or separate computing devices or a combination thereof.
For example, a plurality of the applications described herein may
execute in the same computing device 500, or in multiple computing
devices in the same computing environment 203. Additionally, it is
understood that terms such as "application," "service," "system,"
"engine," "module," and so on may be interchangeable and are not
intended to be limiting.
[0058] Disjunctive language such as the phrase "at least one of X,
Y, or Z," unless specifically stated otherwise, is otherwise
understood with the context as used in general to present that an
item, term, etc., may be either X, Y, or Z, or any combination
thereof (e.g., X, Y, and/or Z). Thus, such disjunctive language is
not generally intended to, and should not, imply that certain
embodiments require at least one of X, at least one of Y, or at
least one of Z to each be present.
[0059] It should be emphasized that the above-described embodiments
of the present disclosure are merely possible examples of
implementations set forth for a clear understanding of the
principles of the disclosure. Many variations and modifications may
be made to the above-described embodiment(s) without departing
substantially from the spirit and principles of the disclosure. All
such modifications and variations are intended to be included
herein within the scope of this disclosure and protected by the
following claims.
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