U.S. patent application number 14/790048 was filed with the patent office on 2015-10-22 for generating suggested search queries.
The applicant listed for this patent is Amazon Technologies, Inc.. Invention is credited to Rahul H. Bhagat.
Application Number | 20150302012 14/790048 |
Document ID | / |
Family ID | 53718957 |
Filed Date | 2015-10-22 |
United States Patent
Application |
20150302012 |
Kind Code |
A1 |
Bhagat; Rahul H. |
October 22, 2015 |
GENERATING SUGGESTED SEARCH QUERIES
Abstract
Disclosed are various embodiments for generating suggested
search queries that are relevant to a user supplied search query. A
user supplied search query is received. Historical search queries
are identified that are relevant and/or similar to the user
supplied search query. The identified historical queries are then
ranked according to various factors.
Inventors: |
Bhagat; Rahul H.; (Bellevue,
WA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Amazon Technologies, Inc. |
Seattle |
WA |
US |
|
|
Family ID: |
53718957 |
Appl. No.: |
14/790048 |
Filed: |
July 2, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
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12965476 |
Dec 10, 2010 |
9098569 |
|
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14790048 |
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Current U.S.
Class: |
707/734 |
Current CPC
Class: |
G06F 16/2425 20190101;
G06F 16/9535 20190101; G06F 16/24578 20190101; G06F 16/248
20190101; G06F 16/3338 20190101; G06Q 30/0256 20130101; Y10S
707/99932 20130101; G06F 16/9558 20190101; G06F 16/3325 20190101;
G06F 16/90324 20190101 |
International
Class: |
G06F 17/30 20060101
G06F017/30 |
Claims
1. A non-transitory computer-readable medium embodying a program
executable in a computing device, the program comprising: code that
receives a user supplied search query, the user supplied search
query comprising a plurality of search terms; code that removes at
least one of the plurality of search terms from the user supplied
search query to generate a plurality of resultant search queries;
code that determines whether individual ones of the plurality of
resultant search queries match a respective historical search query
in a data store accessible to the computing device that is
associated with at least one search result in the data store; code
that identifies the respective historical search query as being
relevant to the user supplied search query by executing at least
one relevance function and at least one similarity function against
an index of the respective historical search queries with the user
supplied search query, wherein the at least one relevance function
comprises a phrase level edit distance comparison of the user
supplied search query to the respective historical search query;
code that generates a ranking of the respective historical search
queries according to a number of search results with which each of
the respective historical search queries is associated, wherein a
first historical search query associated with a higher number of
search results is ranked higher than a second historical search
query associated with a lower number of search results; and code
that generates a user interface displaying the respective
historical search queries in an order according to the ranking.
2. The non-transitory computer-readable medium of claim 1, wherein
the code that identifies the respective historical search query as
being relevant to the user supplied search query further comprises:
code that identifies a plurality of search results associated with
individual ones of the plurality of resultant search queries; and
code that determines whether individual ones of the of the
plurality of search results associated with individual ones of the
plurality of resultant search queries match the at least one search
result in the data store.
3. The non-transitory computer-readable medium of claim 1, wherein
the program further comprises: code that generates a ranking of the
respective historical search queries based at least in part upon
the phrase level edit distance comparison of the user supplied
search query to the respective historical search query.
4. The non-transitory computer-readable medium of claim 1, wherein
the code that generates the user interface displaying the
respective historical search queries further comprises code that
generates a hyperlink associated with individual ones of the
respective historical search queries.
5. A system, comprising: at least one of one or more computing
devices; and a search application executable via at least one of
the one or more computing devices, the search application
comprising: logic that receives a user supplied search query, the
user supplied search query comprising a plurality of search terms;
logic that removes at least one of the plurality of search terms
from the user supplied search query to generate a plurality of
resultant search queries; logic that determines whether individual
ones of the plurality of resultant search queries match a
respective historical search query in a data store accessible to
the at least one of the one or more computing devices that is
associated with at least one search result in the data store; logic
that identifies the respective historical search query as being
relevant to the user supplied search query by executing at least
one relevance function and at least one similarity function against
an index of the respective historical search queries with the user
supplied search query, wherein the at least one relevance function
comprises a phrase level edit distance comparison of the user
supplied search query to the respective historical search query;
logic that generates a ranking of the respective historical search
queries according to a number of search results with which each of
the respective historical search queries is associated, wherein a
first historical search query associated with a higher number of
search results is ranked higher than a second historical search
query associated with a lower number of search results; and logic
that generates a user interface displaying the respective
historical search queries in an order according to the ranking.
6. The system of claim 5, wherein the logic that identifies the
respective historical search query as being relevant to the user
supplied search query further comprises: logic that generates the
ranking of the respective historical search query according to a
number of products with which the respective historical search
query is associated.
7. The system of claim 5, wherein the logic that identifies the
respective historical search query as being relevant to the user
supplied search query further comprises: logic that identifies a
subset of the historical search queries submitted by users over a
predetermined period of time; and logic that indexes the subset of
the historical search queries in the index.
8. The system of claim 5, wherein the logic that generates the user
interface displaying the respective historical search queries
further comprises: logic that encodes for display a subset of the
at least one search result associated with the respective
historical search query in the user interface; and logic that
encodes for display a historical search query hyperlink, the
historical search query hyperlink linking to a search result user
interface displaying the at least one search result associated with
the respective historical search query.
9. The system of claim 5, wherein the logic that identifies the
respective historical search query as being relevant to the user
supplied search query further comprises: logic that generates the
ranking of the respective historical search query according to a
conversion rate of the respective historical search query, the
conversion rate being a rate at which at least one product
associated with the respective historical search query is
purchased.
10. The system of claim 5, wherein the logic that identifies the
respective historical search query as being relevant to the user
supplied search query further comprises: logic that generates the
ranking of the respective historical search query according to a
popularity of the respective historical search query, the
popularity being based at least in part upon a number of users who
submitted the respective historical search query.
11. The system of claim 5, wherein the logic that identifies the
respective historical search query as being relevant to the user
supplied search query further comprises: logic that generates the
ranking of the respective historical search query according to a
popularity of the respective historical search query, the
popularity being based at least in part upon a number of times that
the respective historical search query was executed.
12. The system of claim 11, wherein the search application further
comprises logic that increases a popularity metric associated with
the popularity of the respective historical search query when a
user selects a hyperlink associated with the respective historical
search query and a search result associated with the respective
historical search query.
13. The system of claim 5, wherein the logic that identifies the
respective historical search query as being relevant to the user
supplied search query further comprises: logic that associates at
least one of a marketplace and a product category with the
respective historical search query; and logic that designates the
respective historical search query as being relevant to the user
supplied search query when the user supplied search query is
performed in at least one of the marketplace and the product
category.
14. The system of claim 5, wherein the search application further
comprises logic that assigns a weight to a search term in
individual ones of the resultant search queries; and the logic that
identifies the respective historical search query as being relevant
to the user supplied search query further comprises logic that
generates the ranking of the respective historical search query
according to a number of highest weighted search terms in the
individual ones of the resultant search queries that comprise the
respective historical search query.
15. The system of claim 14, wherein the logic that assigns a weight
to the search term in the individual ones of the resultant search
queries further comprises logic that assigns a higher weight to a
first search term in the individual ones of the resultant search
queries when the first search term is associated with a fewer
number of historical search queries relative to a second search
term in the individual ones of the resultant search queries.
16. A method, comprising: receiving, via at least one of one or
more computing devices, a user supplied search query, the user
supplied search query comprising a plurality of search terms;
removing, via at least one of the one or more computing devices, at
least one of the plurality of search terms from the user supplied
search query to generate a plurality of resultant search queries;
determining, via at least one of the one or more computing devices,
whether individual ones of the plurality of resultant search
queries match a respective historical search query in a data store
accessible to the at least one of the one or more computing devices
that is associated with at least one search result in the data
store; identifying, via at least one of the one or more computing
devices, the respective historical search query as being relevant
to the user supplied search query by executing at least one
relevance function and at least one similarity function against an
index of the respective historical search queries with the user
supplied search query, wherein the at least one relevance function
comprises a phrase level edit distance comparison of the user
supplied search query to the respective historical search query;
generating, via at least one of the one or more computing devices,
a ranking of the respective historical search queries according to
a number of search results with which each of the respective
historical search queries is associated, wherein a first historical
search query associated with a higher number of search results is
ranked higher than a second historical search query associated with
a lower number of search results; and generating, via at least one
of the one or more computing devices, a user interface displaying
the respective historical search queries in an order according to
the ranking.
17. The method of claim 16, wherein generating the user interface
displaying the respective historical search queries further
comprises generating, via at least one of the one or more computing
devices, a hyperlink associated with individual ones of the
respective historical search queries.
18. The method of claim 16, further comprising assigning, via at
least one of the one or more computing devices, a weight to
individual ones of the plurality of search terms, wherein a higher
weight is assigned to a respective one of the plurality of search
terms that is associated with a respective historical search query
that yields a fewest number of search results greater than zero
than a respective one of the plurality of search terms that is
associated with a respective historical search query that yields a
greater number of search results.
19. The method of claim 18, wherein generating the ranking of the
respective historical search queries further comprises assigning,
via at least one of the one or more computing devices, a higher
rank to a first historical search query comprising higher weighted
search terms than a second historical search query.
20. The method of claim 16, further comprising generating, via at
least one of the one or more computing devices, a ranking of the
respective historical search queries based at least in part upon
the phrase level edit distance comparison of the user supplied
search query to the respective historical search query.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of and claims the benefit
of U.S. patent application Ser. No. 12/965,476, entitled
"GENERATING SUGGESTED SEARCH QUERIES," and filed Dec. 10, 2010,
which is hereby incorporated by reference in its entirety.
BACKGROUND
[0002] Search systems can be employed in various settings,
including in a general purpose setting or in an electronic commerce
system. Search systems can surface various items in a data store
based on keyword matching, relevance, similarity, and other
measures. Some search queries submitted by users may not surface
any items in a data store regardless of the matching. In an
electronic commerce system, additional information is known about
search results (e.g., products in a catalog) in a data store.
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, 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] 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, 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.
[0005] FIG. 1 is a drawing of a networked environment including a
computing device executing a search application according to an
embodiment of the present disclosure.
[0006] FIG. 2 is a drawing of a user interface generated by the
computing device of FIG. 1 according to an embodiment of the
present disclosure.
[0007] FIG. 3 is a drawing of a user interface generated by the
computing device of FIG. 1 according to an embodiment of the
present disclosure.
[0008] FIG. 4 is a drawing of a user interface generated by the
computing device of FIG. 1 according to an embodiment of the
present disclosure.
[0009] FIG. 5 is a drawing of a flowchart that illustrates one
example of the operation of a search application executed in the
computing device depicted in FIG. 1 according to an embodiment of
the present disclosure.
[0010] FIG. 6 is a drawing of one example of the computing device
of FIG. 1 according to an embodiment of the present disclosure.
DETAILED DESCRIPTION
[0011] The various embodiments described herein related to
generating suggested search terms that can be employed to locate
one or more items in a data store. In some embodiments, the
suggested search terms can be employed to locate products in an
electronic commerce system. During the interactions of a user with
an electronic commerce system, for example, search queries
submitted by a user to a search engine may yield few and/or no
search results. In some scenarios, search queries submitted by a
user may yield search results that do not result in a high rate of
conversion, or product purchases. Other scenarios can be
appreciated in which it may be desired to provide higher quality
search results to a user of an electronic commerce system.
Accordingly, embodiments of the disclosure described herein relate
to systems and methods of generating suggested queries based at
least upon historical search queries submitted by other users as
well as various metrics and other data about the historical search
queries that are housed in a data store.
[0012] With reference to FIG. 1, shown is a networked environment
100 according to various embodiments. The networked environment 100
includes at least one computing device 103, a data store 105, and
at least one client 106 in communication with the computing device
103 via a network 109. The network 109 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.
[0013] The computing device 103 may comprise, for example, a server
computer or any other system providing computing capability.
Alternatively, a plurality of computing devices 103 may be employed
that are arranged, for example, in one or more server banks or
computer banks or other arrangements. For example, a plurality of
computing devices 103 together may comprise, for example, a cloud
computing resource, a grid computing resource, and/or any other
distributed computing arrangement. Such computing devices 103 may
be located in a single installation or may be dispersed among many
different geographical locations. In one embodiment, the computing
device 103 represents a virtualized computer system executing on
one or more physical computing systems. For purposes of
convenience, the computing device 103 is referred to herein in the
singular. Even though the computing device 103 is referred to in
the singular, it is understood that a plurality of computing
devices 103 may be employed in the various arrangements as
described above.
[0014] Various applications and/or other functionality may be
executed in the computing device 103 according to various
embodiments. Also, various data and/or items are stored in a data
store 105 that is accessible to the computing device 103. The data
store 105 may be representative of a plurality of data stores that
can be geographically disparate and accessible to the computing
device 103 via a network 109, as can be appreciated. As a
non-limiting example, applications facilitating embodiments of this
disclosure can be executed on the computing device 103, and other
devices dedicated to providing the functionality of a data store
105 or data store can be located in a separate installation
accessible to the computing device 103. Additionally, the items
and/or data stored in the data store 105, for example, are
associated with the operation of the various applications and/or
functional entities described below.
[0015] The data store 105, in the non-limiting example of an
electronic commerce system facilitated by the computing device 103,
can include items that are associated with products 108 available
in the electronic commerce system. The data store 105 can also
include other data relevant to products, such as, but not limited
to, the following: product category, title, keywords, description,
price, weight, shipping methods, related images, reviews, similar
items, meta data, hidden text, a list of merchants selling the
item, stock number, other associated categories, page view history,
etc. The data store 105 can also include other data related to
products 108 as can be appreciated, but are not necessary to
discuss herein for an understanding of the various embodiments of
the disclosure. Additionally, in the case of a computing device 103
facilitating a content delivery system other than an electronic
commerce system (e.g., a general purpose search engine, etc.), the
data store 105 can store other data associated with items for which
the content delivery system is suited.
[0016] The data store 105 can also include information about users
of the system. User data 110 can include a user profile associated
with the various users of, for example, an electronic commerce
system facilitated by the computing device 103. Such a user profile
can include data about the user, browsing history, purchase
history, product interests, demographic information, location, a
product wish list, etc. Additionally, user data 110 can store
information about various user sessions that describe the
interactions of a user with the computing device 103. By way of
illustration, purchase history in a user profile can identify each
of the purchases made by users via an electronic commerce system.
As another example, browse history data sets forth the browsing
activity of customers when they visit an electronic commerce
system. The browse history data can include data indicating how a
user has navigated through an electronic commerce system and the
products or communities in which a user has viewed and/or expressed
an interest.
[0017] The data store 105 can also include data about historical
search queries 113. Historical search queries 113 can include
search queries submitted by users in the past that have yielded
search results. Accordingly, query terms 115 that describe the
search terms associated with the historical query 115. Query
associations 117 can also be stored in the data store 105 for each
historical search query 113. A query association 117 can include
meta data associated with the historical search query 113 that can
be used to determine relevance and/or similarity to a search query
submitted by a user to the search application 111, as will be
described in further detail herein. One example of a query
association 117 can be a geographic location associated with the
users who have submitted the historical search query 113 in the
past. Another non-limiting example of a query association 117 can
include a product category or marketplace within an electronic
commerce system in which the historical search query 113 was
submitted by a user. In some embodiments, a query association 117
can include another search query with which a particular search
query should be associated. As one example, the search application
111 may determine that a percentage of users above a predefined
threshold have entered two different queries in a single session.
Accordingly, the search application 111 can designate these two
queries as related. Therefore, a historical search query entry 113
associated with these queries can have a query association 117 that
points to the other.
[0018] Historical search queries can also be associated with
various other metrics 119, which can be stored in the data store
105. Metrics 119 associated with a historical query can include a
number of search results with which the query is associated, a
popularity of the historical search query, a conversion rate
associated with the query, and other metrics as can be appreciated.
In one embodiment, a conversion rate associated with a historical
query can be based at least upon a percentage of users in an
electronic commerce system that purchase a product that is a search
result associated with the historical query.
[0019] Various other behavioral data can also be stored as metrics
119 associated with the query. In some embodiments, the search
application 111 or other application can track user behavior in a
session, relate this behavior to search terms entered by the user
during the session, and store the data as a metric 119. As one
example, the search application 111 can track an amount of time a
user spends browsing search results after a search query is
submitted to the search application 111 and search results returned
to the user. In one example, if a user spends more time browsing
search results relative to other search queries, it may be deduced
that the search query returned relevant results that held the
user's attention. As another example, the search application 111
can track whether a user adds a search result that is a product to
a virtual shopping cart in an electronic commerce system. The
search application 111 can deduce from this behavior that the
search query provided relevant search results.
[0020] The computing device 103 is configured to execute various
applications such as, for example, an application server 110 and a
search application 111, and potentially other applications. In one
embodiment, an application server 110 is executed to provide for
interaction between the applications on the computing device 103
and clients 106 and/or mobile devices 107 as will be described. To
this end, the application server 110 may also include, for example,
a web server application or similar application as can be
appreciated. Other systems and/or applications facilitated or
executed by an application server 110 may also include, but are not
limited to, order fulfillment systems, dynamic network or web page
servers, inventory systems, or other systems as can be appreciated.
However, such systems are not described herein in detail.
[0021] Users of the search application 111, whether in the context
of an electronic commerce system, a general purpose search engine,
or other system, may attempt to use search terms or search phrases
to locate one or more items in the data store 105. In the depicted
non-limiting embodiment, users of the search application 111 may
submit search queries to the search application 111 to attempt to
locate products available via an electronic commerce system
facilitated by the computing device 103.
[0022] The client 106 and mobile device 107 are representative of a
plurality of devices that may be coupled to the network 109. The
client 106 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, a personal digital
assistant, a cellular telephone, set-top box, music players, web
pads, tablet computer systems, or other devices with like
capability.
[0023] The client 106 may be configured to execute various
applications such as a browser 123 and/or other applications. The
browser 123 may be executed in a client 106, for example, to access
and render network pages 126, such as web pages, or other content
served up by the computing device 103 and/or other servers. The
client 106 may be configured to execute applications beyond a
browser 123 such as, for example, email applications, instant
message applications, and/or other applications. Accordingly, in
some embodiments a user can manipulate a user interface presented
in the form of network pages 126 shown on a display device 151 via
the browser 123 or other application that causes interaction with
the application server 110 executed by the computing device 103.
The application server 110 executed on the computing device 103 can
facilitate the generation of user interfaces on a client 106 by
transmitting data to the client 106 that can be rendered by a
browser 123 or other application to create the various user
interfaces.
[0024] Another example of a device that can interact with the
search application 111 includes a mobile device 107, which can
execute a mobile application 155 such as a browser that can render
network pages generated by the search application 111. In another
embodiment, the mobile application 155 can be tailored to access
data provided by the search application 111 and can include client
side code that generates a user interface on a display device of
the mobile device 107. Accordingly, a user can submit questions to
the search application 111 as well as browse and/or submit
responses to questions published by the search application 111 via
the mobile application 155. The mobile device 107 may comprise a
mobile device including cellular telephone and data access,
location detection hardware, and other hardware and software
components. The mobile device 107 can detect the location of a user
using global positioning system (GPS) or other location detection
functionality, which can be submitted by the mobile application 155
to the search application 111. In one example, global positioning
system (GPS) functionality provided by the mobile device 107 can
provide a location of the client to the mobile application 155,
which can in turn transmit a location of the client to the search
application 111. In one embodiment, the search application 111 can
utilize location based services and applications executed on the
mobile device 107 to determine a location of the user, which can,
in some embodiments, be employed to assist with generating
suggested search queries.
[0025] It should also be appreciated that a client of the search
application 111 can be another software module that facilitates
communication with a client 106 or mobile device 107. As one
example, the search application 111 can provide an application
programming interface (API) through which another software
application can access the functionality of the search application
111. In one embodiment, a presentation layer module may interact
with the search application 111 by submitting a search request to a
search application 111 API, which can respond with a search
response that includes various search results. Other variations
should be appreciated by a person of ordinary skill in the art.
[0026] Therefore, in the context of the non-limiting exemplary
framework presented above, in order to facilitate embodiments of
the present disclosure, the search application 111 is executed to
collect and process information relating to user search queries
regarding related products, product categories, and/or other data
accessible to the computing device 103. To this end, the search
application 111 can facilitate the generating of a search term user
interface element that allows a user to submit search terms for
items the user wishes the locate in the data store 105. In
addition, the search application 111 can provide suggested search
terms to a user based at least upon characters entered in a search
term user interface provided by the search application 111 on a
client or mobile device.
[0027] The search application 111 can employ various algorithms
that take into account various factors and data to generate search
query suggestions in response to a search query received from a
client. Additionally, there are numerous practical applications of
the generating of suggested search queries, as will be described
herein. In one embodiment, upon receiving a search query from a
client or mobile device, the search application 111 can determine
whether the search query is associated with any search results in
the data store 105. In the case of an electronic commerce system
facilitated by the at least one computing device 103, the search
application 111 can determine whether the search query is
associated with any products 147 in the data store 105. As can be
appreciated, to make such a determination, the search application
111 can execute a similarity and/or relevance algorithm against a
search index that indexes various data regarding the products
147.
[0028] If, in the above example, there are no products associated
with the search query in the data store 105, the search application
111 can identify whether there are historical search queries 113
that are relevant and/or similar to the search query that are
associated with search results and/or products in the data store
105. If there are historical search queries 113 that are relevant
and/or similar to the search query, the search application 111 can
generate a user interface, such as a network page, that includes
one or more of these historical search queries 113 as well as one
or more of their associated search results.
[0029] In one embodiment of this disclosure, in order to identify
similar and/or relevant historical search queries, the search
application 111 can determine if there are historical search
queries 113 that are associated with search results in the data
store 105 by removing one or more search term from the search
query. The search application 111 can examine the various
permutations of resultant queries that result from the removal of
search terms from the search query and determine if they match
search terms of a historical search query 113 that is associated
with search results. If the resultant search queries are associated
with search results, they can be identified as potentially similar
and/or relevant historical search queries 113 relative to the
original search query. The search application 111 can then rank the
historical search queries 113 according to a number of search
results associated therewith. As one example, a historical search
query 113 so identified that is associated with the most search
results can be designated as the highest ranked historical search
query 113 relative to the user supplied search query.
[0030] In some embodiments, as described above, the search
application 111 can remove search terms from a user supplied search
query until an exact match is found as a historical search query
113 that is associated with search results in the data store. In
one embodiment of such a function, the search application 111 can
be limited to only remove one search term from the user supplied
search query. For example, if a user supplied four term search
query that yields no products when a search of the data store is
executed using the search query, the search application 111 can
determine whether there are three term historical search queries
113 using any three of the four terms that are associated with at
least one search result. In this way, the likelihood that search
application 111 yields search results that are not relevant to the
search query is reduced.
[0031] In another embodiment, the search application 111 can
identify historical queries similar and/or relevant historical
search queries 113 by calculating a phrase level edit distance of
the search query relative to historical search queries 113. A
phrase level edit distance as can be implemented in embodiments of
the disclosure by determining a number of phrase or word
substitutions, or word additions and/or deletions, required to
transform a search query submitted by a user into a historical
query 113 in the data store 105. Accordingly, a historical query
requiring the fewest number of word substitutions to arrive at the
search query entered by a user can be ranked as the most similar
and/or relevant historical search query.
[0032] The search application 111 can also identify relevant and/or
similar historical search queries in the data store 105 by
performing various text similarity functions. The search
application 111 can determine relevance and/or similarity by
calculating a cosine similarity, jaccad similarity, dice
similarity, and other textual similarity functions as can be
appreciated. Accordingly, in the case of a search query submitted
by a user that yields no search results, the search application 111
can employ one or more textual similarity functions to identify the
most similar historical search query 113 that is associated with a
search result, and generate a user interface with one or more of
the most similar historical search queries 113.
[0033] The search application 111 can also identify the importance
of words in a user supplied search query and assign a weight to
each of the words according to its importance. Accordingly, the
search application 111 can then identify a similar and/or relevant
historical search query 113 using a vector based similarity
function. In one embodiment, in the case of a multi-word user
supplied search query, the search application 111 can determine
whether the individual words in the search query constitute a
historical query 113 in the data store 105 that is associated with
one or more search results. The search application 111 can then
assign a higher weight to a word in the search query that is
associated with a fewer number of search results greater than one.
In this way, common words that may be associated with a large
number of search results are weighted less, as it can be deduced
that those search terms that are associated with fewer search
results are more likely to yield a search result that is relevant
to the user supplied search query.
[0034] The search application 111 can also rank the identified
historical search queries 113 in various other ways independent of
textual similarity that can facilitate the identification of a
historical search query 113 that can be provided to a user,
particularly in the case of a user supplied search query that
yields no search results. As described above, historical search
queries 113 that are identified as relevant and/or similar to a
user supplied search query can be ranked according to a number of
search results with which they are associated. Historical search
queries 113 that are identified by the search application 111 can
also be ranked according to a conversion rate of the historical
search query. In other words, the search application 111 can rank a
historical search query 113 in an electronic commerce system that
yields in the highest number of purchases, profits, revenue, or
other metrics.
[0035] Historical search queries 113 that are identified by the
search application 111 can also be ranked by popularity. In other
words, the search application 111 can rank a historical search
query 113 submitted by the number of users who submitted the query,
the number of times the query was executed, or other aggregate
metrics. Historical search queries 113 that are identified by the
search application 111 can also be ranked according to their query
associations 117. For example, if a user supplied search query is
submitted with a filter, the search application 111 can rank a
historical search query 113 associated with the same filter higher
than other historical search queries. In the case of an electronic
commerce system facilitating multiple marketplaces as well as
multiple product categories, one example of a filter can be the
marketplace and/or product category filter supplied by the user
when submitting the search query.
[0036] The search application 111 can identify relevant and/or
similar historical search queries 113 relative to a user supplied
search query by applying one of the above methods. Additionally,
the search application 111 can also apply any combination of the
above factors and weight the factors in various ways. As one
example, the search application 111 can identify relevant
historical queries by removing search terms until an exact match of
a historical query yielding search results is found. As noted
above, because the search application 111 can perform such a
process on the various permutations of queries that would result
from removing one search term from a multi-term search query, this
may result in multiple historical search queries that yield search
results. Accordingly, in one example, the search application 111
can generate a ranking of the historical search queries according
to popularity, conversion rate, a marketplace association, and any
other factor as can be appreciated.
[0037] Additionally, the search application 111 can restrict the
historical search queries 113 that are analyzed to a particular
time period. As one non-limiting example, the search application
111 can analyze historical search queries 113 in the data store 105
that were submitted by other users in the thirty days previous to
the time the user supplied search query is received.
[0038] Having described various ways that historical search queries
113 that are similar and/or relevant to a user supplied search
query can be identified, reference is now made to FIG. 2, which
depicts a user interface that can be facilitated by the search
application 111 in various embodiments of the disclosure. The user
interfaces shown in FIGS. 2-4 can be generated by the search
application 111 or other software module in association with the
search application 111. As one non-limiting example, a presentation
layer can generate a network page in a presentation language and
encodes for display search results and other data regarding search
queries generated by the search application 111.
[0039] The non-limiting user interface example shown in FIG. 2
shows one application of the way in which historical search queries
113 identified by the search application 111 can be employed to
generate search results for a user. In the depicted example, a
search query received by the search application in a search term
user interface element 201 yields no search results. In the context
of an electronic commerce system facilitated by a computing device
103 executing the search application 111, the search query is not
associated with any products available via the electronic commerce
system.
[0040] Accordingly, in response to a search query that does not
yield any product search results, the search application can
identify similar and/or relevant historical search queries 113 in a
data store 105. In the depicted example, the search application
removes a search term from the user supplied search query, and
determines whether the various permutations of the resultant query
are stored in the data store 105 as a historical search query 113
that is in turn associated with product search results. In FIG. 2,
the search application also ranks the historical queries according
to a number of product search results with which the historical
search query 113 is associated. Accordingly, the search application
111 facilitates generation of a user interface that includes the
historical search queries 113 displayed in a ranked order according
to the number of product search results with which they are
associated. The search application 111 can also facilitate
generation of a user interface that displays a subset of search
results with each of the historical queries 113 identified by the
search application 111.
[0041] Reference is now made to FIG. 3, which depicts an
alternative example of a user interface facilitated by the search
application 111. In FIG. 3, a user supplied query is associated
with a number of search results, and the search application 111 can
identify historical search queries 113 that are relevant and/or
similar to the user supplied search query to supplement the user
interface with additional search results 301. In the depicted
example, the search application 111 identifies related historical
search queries 113 by removing a search term from the user supplied
search query and determining whether the resultant query
corresponds to a historical search query 113. In the depicted
example, the search application 111 can facilitate generation of a
user interface that displays search results corresponding to the
highest ranked historical search queries 113. As described above, a
historical search query 113 that is related to a user supplied
search query can be ranked according to various factors, such as,
popularity, conversion rate of associated search results,
profitability of a product search result, and other factors as can
be appreciated.
[0042] FIG. 4 depicts an alternative example of a user interface
that can be facilitated by the search application 111. In the
example of FIG. 4, the user supplied search query is associated
with product search results in an electronic commerce system. The
search application 111 can be employed to identify historical
search queries 113 that are similar and/or relevant to the user
supplied search query as described above. In the depicted example,
the search application 111 can facilitate generation of a user
interface that includes hyperlinks to historical search queries 113
that are similar and/or relevant to the user supplied search query.
Additionally, the search application 111 can determine from a user
session whether the user follows a hyperlink that is displayed and
create a query association 117 between the user supplied search
query and the historical query 113 associated with the hyperlink,
which can facilitate display of higher quality historical search
queries 113 for other users. The search application 111 can also
track other attributes of a user session in this regard as
described above.
[0043] Referring next to FIG. 5, shown is a flowchart that provides
one example of the operation of a portion of the search application
111 according to various embodiments. It is understood that the
flowchart of FIG. 5 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 search application
111 as described herein. As an alternative, the flowchart of FIG. 5
may be viewed as depicting an example of steps of a method
implemented in the computing device 103 (FIG. 1) according to one
or more embodiments.
[0044] Beginning with box 501, the search application 111 receives
a user supplied search query having at least one search term. In
box 503, the search application 111 identifies at least one
historical search query that is similar and/or relevant to the user
supplied search query, and in box 505, the search application 111
ranks the identified historical search queries according to various
factors and/or metrics that yield search results that are relevant
and/or similar to the user supplied search query. As described
above, the search application 111 can determine relevance and/or
similarity by executing a textual similarity function to identify
historical queries 113 that have the most textual similarity to the
user supplied search query.
[0045] As one example, the search application 111 can also remove a
search term from the user supplied search query and determine
whether a historical search query 113 is associated with the
resultant search query. The search application 111 can also
determine a phrase level edit distance of historical search queries
113 from the user supplied search query, or any other textual
similarity function described above. The search application 111 can
rank search results according to various factors and/or metrics as
described above. The search application 111 can identify a
marketplace or other filter applied to the user supplied search,
and rank historical search queries 113 performed in associated with
the same filter higher than those that are not. The search
application 111 can also rank the historical search queries 113
identified as relevant and/or similar to the search query according
to other metrics and/or factors, including, but not limited to,
popularity, conversion rate, click-through rate, and other factors
as described above. Additionally, the historical search queries 113
can be ranked based on a combination of various factors, where each
factor can be weighted to generate such a ranking.
[0046] With reference to FIG. 6, shown is a schematic block diagram
of the computing device 103 according to an embodiment of the
present disclosure. The computing device 103 includes at least one
processor circuit, for example, having a processor 603 and a memory
606, both of which are coupled to a local interface 609. To this
end, the computing device 103 may comprise, for example, at least
one server computer or like device. The local interface 609 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 606 are both data and several
components that are executable by the processor 603. In particular,
stored in the memory 606 and executable by the processor 603 are
the application server 110, search application 111, and potentially
other applications. Also stored in the memory 606 may be a data
store 105 and other data. In addition, an operating system may be
stored in the memory 606 and executable by the processor 603.
[0048] It is understood that there may be other applications that
are stored in the memory 606 and are executable by the processors
603 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, Javascript, Perl, PHP, Visual Basic, Python,
Ruby, Delphi, Flash, or other programming languages.
[0049] A number of software components are stored in the memory 606
and are executable by the processor 603. In this respect, the term
"executable" means a program file that is in a form that can
ultimately be run by the processor 603. 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 606 and run by the processor
603, 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 606 and executed by the processor 603, or
source code that may be interpreted by another executable program
to generate instructions in a random access portion of the memory
606 to be executed by the processor 603, etc. An executable program
may be stored in any portion or component of the memory 606
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 606 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 606 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 603 may represent multiple processors
603 and the memory 606 may represent multiple memories 606 that
operate in parallel processing circuits, respectively. In such a
case, the local interface 609 may be an appropriate network 109
(FIG. 1) that facilitates communication between any two of the
multiple processors 603, between any processor 603 and any of the
memories 606, or between any two of the memories 606, etc. The
local interface 609 may comprise additional systems designed to
coordinate this communication, including, for example, performing
load balancing. The processor 603 may be of electrical or of some
other available construction.
[0052] Although the search application 111 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 having appropriate logic gates, 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 flowchart of FIG. 5 shows the functionality and
operation of an implementation of portions of the search
application 111. 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 603
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 flowchart of FIG. 5 shows 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 FIG. 5 may be
executed concurrently or with partial concurrence. Further, in some
embodiments, one or more of the blocks shown in FIG. 5 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 search application 111, 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 603 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. 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.
[0056] 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.
* * * * *