U.S. patent application number 15/798175 was filed with the patent office on 2018-02-15 for related entities.
The applicant listed for this patent is Google Inc.. Invention is credited to Omer Bar-or, Grace Chung, Christina R. Dhanaraj, Nathaniel J. Gaylinn, Kavi J. Goel, Pravir K. Gupta, Peter Jin Hong, Ramakrishnan Kazhiyur-Mannar, Jared L. Levy, Jack W. Menzel, Shashidhar A. Thakur, Benson Tsai.
Application Number | 20180046717 15/798175 |
Document ID | / |
Family ID | 47891962 |
Filed Date | 2018-02-15 |
United States Patent
Application |
20180046717 |
Kind Code |
A1 |
Hong; Peter Jin ; et
al. |
February 15, 2018 |
RELATED ENTITIES
Abstract
Methods, systems, and apparatus, including computer programs
encoded on computer storage media, for identifying entities that
are related to an entity to which a search query is directed. One
of the methods includes receiving a search query, wherein the
search query has been determined to relate to a first entity of a
first entity type, and wherein one or more entities of a second
entity type have a relationship with the first entity; receiving
search results for the search query; determining that a count of
search results identifying a resource containing a reference to the
first entity satisfies a first threshold value; determining that a
count of search results identifying a resource having the second
entity type as a relevant entity type satisfies a second threshold
value; and transmitting information identifying the one or more
entities of the second entity type as part of the response to the
search query.
Inventors: |
Hong; Peter Jin; (San
Francisco, CA) ; Gupta; Pravir K.; (Mountain View,
CA) ; Gaylinn; Nathaniel J.; (Mountain View, CA)
; Kazhiyur-Mannar; Ramakrishnan; (Milpitas, CA) ;
Goel; Kavi J.; (San Francisco, CA) ; Bar-or;
Omer; (Mountain View, CA) ; Menzel; Jack W.;
(Mountain View, CA) ; Dhanaraj; Christina R.;
(Sunnyvale, CA) ; Levy; Jared L.; (Mountain View,
CA) ; Thakur; Shashidhar A.; (Saratoga, CA) ;
Chung; Grace; (Zetland, AU) ; Tsai; Benson;
(Sunnyvale, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Google Inc. |
Mountain View |
CA |
US |
|
|
Family ID: |
47891962 |
Appl. No.: |
15/798175 |
Filed: |
October 30, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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15055427 |
Feb 26, 2016 |
9830390 |
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15798175 |
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13774896 |
Feb 22, 2013 |
9275152 |
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15055427 |
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61601975 |
Feb 22, 2012 |
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61647977 |
May 16, 2012 |
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61660637 |
Jun 15, 2012 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 16/951 20190101;
G06F 16/24578 20190101; G06F 16/9535 20190101 |
International
Class: |
G06F 17/30 20060101
G06F017/30 |
Claims
1-20. (canceled)
21. A method performed by one or more computers, the method
comprising: obtaining data identifying a first entity of a first
entity type; identifying a plurality of second entities of the
first entity type that are related to the first entity; determining
a respective ranking score for each of the second entities of the
plurality of second entities of the first entity type; ordering the
second entities of the first entity type according the ranking
scores; and generating a mapping from the first entity to each of
the second entities based on the ordering of the second
entities.
22. The method of claim 21, further comprising: receiving a search
query from a user device, wherein the search query has been
determined to relate to the first entity of the first entity type;
in response to the search query, transmitting, to the user device,
i) search results responsive to the search query and ii)
information identifying an order of the second entities of the
first entity type that matches the ordering.
23. The method of claim 22, wherein the mapping defines the order
of the second entities of the first entity type in response to
received search queries that match the ordering.
24. The method of claim 21, wherein identifying the plurality of
second entities further comprises: identifying the plurality of
second entities based on each of the second entities having a
frequency of co-occurrence with the first entity in resources of an
index of resources greater than a threshold.
25. The method of claim 24, further comprising: determining, for
each second entity, a co-occurrence score for the second entity
based on the frequency of co-occurrence with the first entity in
resources of the index of resources, wherein the ranking score for
each of the second entities is based on the respective
co-occurrence score for the respective second entity.
26. The method of claim 21, further comprising: determining, for
each second entity, a subsequent query score for the second entity
based a frequency of queries for the second entity after a
submission of a query directed to the first entity, wherein the
ranking score for each of the second entities is based on the
respective subsequent query score for the respective second
entity.
27. The method of claim 24, further comprising: determining, for
each second entity, a co-occurrence score for the second entity
based on the frequency of co-occurrence with the first entity in
resources of an index of resources, determining, for each second
entity, a subsequent query score for the second entity based a
frequency of queries for the second entity after a submission of a
query directed to the first entity, wherein the ranking score for
each of the second entities is based on the respective
co-occurrence score and the respective subsequent query score for
the respective second entity.
28. A system comprising one or more computers and one or more
storage devices storing instructions that when executed by the one
or more computers cause the one or more computers to perform
operations comprising: obtaining data identifying a first entity of
a first entity type; identifying a plurality of second entities of
the first entity type that are related to the first entity;
determining a respective ranking score for each of the second
entities of the plurality of second entities of the first entity
type; ordering the second entities of the first entity type
according the ranking scores; and generating a mapping from the
first entity to each of the second entities based on the ordering
of the second entities.
29. The system of claim 28, the operations further comprising:
receiving a search query from a user device, wherein the search
query has been determined to relate to the first entity of the
first entity type; in response to the search query, transmitting,
to the user device, i) search results responsive to the search
query and ii) information identifying an order of the second
entities of the first entity type that matches the ordering.
30. The system of claim 29, wherein the mapping defines the order
of the second entities of the first entity type in response to
received search queries that match the ordering.
31. The system of claim 28, wherein identifying the plurality of
second entities further comprises: identifying the plurality of
second entities based on each of the second entities having a
frequency of co-occurrence with the first entity in resources of an
index of resources greater than a threshold.
32. The system of claim 31, the operations further comprising:
determining, for each second entity, a co-occurrence score for the
second entity based on the frequency of co-occurrence with the
first entity in resources of the index of resources, wherein the
ranking score for each of the second entities is based on the
respective co-occurrence score for the respective second
entity.
33. The system of claim 28, the operations further comprising:
determining, for each second entity, a subsequent query score for
the second entity based a frequency of queries for the second
entity after a submission of a query directed to the first entity,
wherein the ranking score for each of the second entities is based
on the respective subsequent query score for the respective second
entity.
34. The system of claim 31, the operations further comprising:
determining, for each second entity, a co-occurrence score for the
second entity based on the frequency of co-occurrence with the
first entity in resources of an index of resources, determining,
for each second entity, a subsequent query score for the second
entity based a frequency of queries for the second entity after a
submission of a query directed to the first entity, wherein the
ranking score for each of the second entities is based on the
respective co-occurrence score and the respective subsequent query
score for the respective second entity.
35. One or more non-transitory computer storage media storing
instructions that when executed by one or more computers cause the
one or more computers to perform operations comprising: obtaining
data identifying a first entity of a first entity type; identifying
a plurality of second entities of the first entity type that are
related to the first entity; determining a respective ranking score
for each of the second entities of the plurality of second entities
of the first entity type; ordering the second entities of the first
entity type according the ranking scores; and generating a mapping
from the first entity to each of the second entities based on the
ordering of the second entities.
36. The computer storage media of claim 35, the operations further
comprising: receiving a search query from a user device, wherein
the search query has been determined to relate to the first entity
of the first entity type; in response to the search query,
transmitting, to the user device, i) search results responsive to
the search query and ii) information identifying an order of the
second entities of the first entity type that matches the
ordering.
37. The computer storage media of claim 36, wherein the mapping
defines the order of the second entities of the first entity type
in response to received search queries that match the ordering.
38. The computer storage media of claim 35, wherein identifying the
plurality of second entities further comprises: identifying the
plurality of second entities based on each of the second entities
having a frequency of co-occurrence with the first entity in
resources of an index of resources greater than a threshold.
39. The computer storage media of claim 38, the operations further
comprising: determining, for each second entity, a co-occurrence
score for the second entity based on the frequency of co-occurrence
with the first entity in resources of the index of resources,
wherein the ranking score for each of the second entities is based
on the respective co-occurrence score for the respective second
entity.
40. The computer storage media of claim 35, the operations further
comprising: determining, for each second entity, a subsequent query
score for the second entity based a frequency of queries for the
second entity after a submission of a query directed to the first
entity, wherein the ranking score for each of the second entities
is based on the respective subsequent query score for the
respective second entity.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of application Ser. No.
15/055,427, filed on Feb. 26, 2016, which is a continuation of
application Ser. No. 13/774,896, filed on Feb. 22, 2013, now U.S.
Pat. No. 9,275,152, entitled "Related Entities," which claims the
benefit under 35 U.S.C. .sctn.119(e) of U.S. patent application
Ser. No. 61/601,975, filed Feb. 22, 2012, entitled "Related
Entities," U.S. patent application Ser. No. 61/647,977, filed May
16, 2012, entitled "Related Entities," and U.S. patent application
Ser. No. 61/660,637, filed Jun. 15, 2012, entitled "Related
Entities," all of which are incorporated by reference herein in
their entirety.
BACKGROUND
[0002] This specification relates to Internet search systems.
[0003] Internet search engines aim to identify Internet resources,
e.g., web pages, images, text documents, or multimedia content,
that are relevant to a user's needs and to present information
about the resources in a manner that is most useful to the user.
Internet search engines return a set of search results in response
to a user submitted query. Internet search engines generally
include one or more services that can classify particular received
queries. Such services may include services that classify queries
as one or more of: a query that is pornographic, i.e., is seeking
pornographic results or for which a large number of search results
identifying resources that have been classified as pornographic are
returned; a query that is navigational to a particular resource,
i.e., is seeking that particular resource; a query that is a local
query, i.e., is seeking information about a business located near
the user; or a query that is seeking a particular item of
information, e.g., is looking for an item of information that is an
answer to a question posed in the query.
SUMMARY
[0004] This specification describes technologies relating to
identifying entities that are related to an entity to which a
search query is directed.
[0005] In general, one innovative aspect of the subject matter
described in this specification can be embodied in methods that
include the actions of receiving a first search query from a user
device, wherein the first search query has been determined to
relate to a first entity of a first entity type, and wherein one or
more entities of a second entity type have a predetermined
relationship with the first entity; receiving search results for
the first search query provided by a search engine, wherein each of
the search results identifies a respective resource; determining
that a count of search results identifying a resource containing a
reference to the first entity satisfies a first threshold value;
determining that a count of search results identifying a resource
having the second entity type as a relevant entity type satisfies a
second threshold value; and transmitting information identifying
the one or more entities of the second entity type to the user
device as part of the response to the first search query.
[0006] Other embodiments of this aspect include corresponding
computer systems, apparatus, and computer programs recorded on one
or more computer storage devices, each configured to perform the
actions of the methods. A system of one or more computers can be
configured to perform particular operations or actions by virtue of
having software, firmware, hardware, or a combination of them
installed on the system that in operation causes or cause the
system to perform the actions. One or more computer programs can be
configured to perform particular operations or actions by virtue of
including instructions that, when executed by data processing
apparatus, cause the apparatus to perform the actions.
[0007] These and other embodiments can optionally include one or
more of the following features. Each of the search results can
include a respective title and a respective snippet of text
extracted from the respective resource identified by the search
result, and determining that the count of search results
identifying a resource containing a reference to the first entity
satisfies the first threshold value can include: determining that a
count of search results that include a reference to the first
entity in the respective title or the respective snippet of text
included in the search result satisfies the first threshold
value.
[0008] The information identifying the one or more entities of the
second entity type can include a respective image corresponding to
each of the one or more entities, and the method can further
include: obtaining, for each of the one or more entities of the
second entity type, the respective image corresponding to the
entity from an image search engine in response to a search query
derived from the name of the entity.
[0009] Obtaining the image for a particular entity of the one or
more entities of the second type can include: determining that a
particular search query including the name of the particular entity
is ambiguous, comprising determining, from search results provided
for the particular search query by the search engine, that the
particular search query either does not relate to any entity in an
index that maps each of a plurality of resources to a specific
entity of a specific type or relates to more than one entity in the
index; generating a second search query that includes the name of
the particular entity and at least one of: a reference to the first
entity of the first entity type or a reference to the second entity
type; obtaining image search results for the second search query
from the image search engine; and selecting the image for the
particular entity from images identified by the image search
results for the second search query.
[0010] The method can further include: determining that the second
search query is not ambiguous.
[0011] Selecting the image for the particular entity from images
identified by the image search results can include: selecting the
image based at least in part on an aspect ratio of the image.
[0012] The method can further include: determining from the search
results for the first search query that the first search query
relates to the first entity of the first entity type, including:
determining, using an index that maps each of a plurality of
resources to a specific entity of a specific type, that a count of
search results that identify a resource that is mapped to the first
entity exceeds a third threshold value.
[0013] The method can further include: obtaining data that
classifies the search query as not being any of a query that is
pornographic, a query that is navigational to a particular
resource, a local query, or a query that is seeking a particular
item of information.
[0014] The information identifying the one or more entities can
include information identifying a name of each of the one or more
entities and the second entity type.
[0015] The method can further include: determining a respective
ranking score for each of the entities of the second entity type;
and ordering the entities of the second entity type according to
the ranking scores.
[0016] The ranking score for a particular entity of the second
entity type can be based at least in part on how frequently a
recognized reference to the particular entity co-occurs with a
recognized reference to the first entity in resources indexed by an
indexing engine.
[0017] The ranking score for a particular entity of the second
entity type can be based at least in part on how frequently the
particular entity is searched for by users after submitting a
search query directed to the first entity.
[0018] The ranking score for a particular entity of the second
entity type can be based at least in part on a global popularity of
the particular entity.
[0019] The ranking score for a particular entity of the second
entity type can be based at least in part on how frequently a
recognized reference to the particular entity co-occurs in a same
previously submitted search query as a recognized reference to the
first entity.
[0020] The method can further include: accessing data that
indicates that two or more of the entities of the second entity
type are members of a set of entities that has a specified order;
and adjusting the ordering of the two or more entities of the
second entity type to match the specified order.
[0021] The method can further include: accessing data that
indicates that two or more of the entities of the second entity
type are better known as being part of a broader entity; and
replacing the two or more entities of the second entity type with
the broader entity in the ordering of the entities of the second
entity type.
[0022] The subject matter described in this specification can be
implemented in particular embodiments so as to realize one or more
of the following advantages. Users can easily view information
about entities that have a particular relationship with an entity
to which their search query is directed. In particular, users can
easily obtain information identifying entities that are related to
an entity of interest by submitting a search query that identifies
the entity of interest to a search engine. Additionally, a user can
easily submit another search query to obtain more information about
the related entities. A user can learn about an entity to which
their search query is directed by viewing information about the
entities that are related to the entity. For example, a user can
learn that a particular person is an author by submitting a query
that includes the name of the particular person to a search engine
and being presented with information identifying books written by
the particular person. Additionally, questions that users will
likely have about an entity after submitting a query directed to
the entity can be predicted and information about entities that are
answers to those questions can be provided to the user as part of a
response to the query, e.g., without the user having to submit
another search query or navigate to another resource to seek out
the answers. For example, users submitting queries directed to an
author may frequently subsequently look for information about
particular books written by the author. Information identifying
those particular books can be presented to the user as part of a
response to the search query without the user having to submit
additional queries or navigate to resources identified by the
search results for the query. By submitting a search query directed
to an entity of a particular type, a user can easily obtain
information about, and submit queries directed to, other entities
of the particular type that relate to the entity.
[0023] The details of one or more embodiments of the subject matter
of this specification are set forth in the accompanying drawings
and the description below. Other features, aspects, and advantages
of the subject matter will become apparent from the description,
the drawings, and the claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0024] FIG. 1 shows an example search results page.
[0025] FIG. 2 is a block diagram of an example search system.
[0026] FIG. 3 is a flow diagram of an example process for
identifying one or more related entities to be identified as part
of a response to a search query.
[0027] FIG. 4 is a flow diagram of an example process for
determining whether a search query is directed to a particular
entity.
[0028] FIG. 5 is a flow diagram of an example process for
determining whether related entities should be identified in a
response to a particular search query.
[0029] FIG. 6 is a flow diagram of an example process for building
indices to be used in selecting relevant entities.
[0030] FIG. 7 is a flow diagram of an example process for ordering
related entities.
[0031] FIG. 8 is a flow diagram of an example process for mapping
an entity to related entities of the same type.
[0032] Like reference numbers and designations in the various
drawings indicate like elements.
DETAILED DESCRIPTION
[0033] FIG. 1 shows an example search results page 100 for a search
query 102 "roald dahl." The search results page 100 includes two
search results 104 and 106 and names of related entities 108. The
search results 104 and 106 and the names of related entities 108
are generated by a search system in response to the search query
102. The search results 104 and 106 each identify a respective
resource and include respective titles 120 and 122 and respective
text snippets 124 and 126 that are extracted from the resources
identified by the search results. The search system generates the
search results 104 and 106 using conventional search
techniques.
[0034] The search system classifies the search query 102 as being
directed to a particular entity, i.e., the author Roald Dahl, and
returns names of related entities 108 that have a predetermined
relationship with the particular entity, i.e., that are books
authored by Roald Dahl, for presentation in the search results page
100. In the illustrated example, the search system may classify the
search query 102 as being directed to the author Roald Dahl because
one or both of the search results 104 and 106 identify a resource
that has been determined to be an authoritative resource for the
author Roald Dahl. For example, one or both of the resources
identified by the search results 104 and 106, i.e., the official
web site of the author Roald Dahl and the Wikipedia page for the
author Roald Dahl, may have been determined to be an authoritative
resource for the author Roald Dahl. In response to the search query
102, the search system selects the names of the related entities
that are to be returned, e.g., using an index that stores data
identifying entities that have a relationship with the author Roald
Dahl.
[0035] Each name in the names of related entities 108, e.g.,
"Charlie and the Chocolate Factory" and "James and the Giant
Peach," is presented in the form of a link by which a user can
obtain search results for a query derived from the name of the
related entity. For example, the query derived from the name of the
related entity can include one or more of the name of the related
entity, e.g., "Charlie and the Chocolate Factory," the text of the
search query 102, e.g., "Roald Dahl," and the name of the entity
type to which the name belongs, e.g., "book." Each name is
presented with an image 114 that corresponds to the name, e.g., an
image of the front cover of the book. Each of the images may also
be presented in the form of a link by which a user can get search
results for the query derived from the name of the related entity
to which the image corresponds. In some implementations, in
response to a user hovering a cursor of an input device over one of
the images 114, additional information about the related entity to
which the image corresponds is displayed. For example, in response
to a user hovering over one of the images 114, the year that the
book to which that image corresponds was published could be
displayed to the user.
[0036] The search results page also includes information 110
identifying the type of the related entities, in this case "books,"
named in the search results page 100 and information 112
identifying the entity to which the search query 102 was determined
to relate, in this case, "Roald Dahl."
[0037] FIG. 2 is a block diagram of an example search system 214.
The search system 214 is an example of an information retrieval
system implemented as computer programs on one or more computers in
one or more locations, in which the systems, components, and
techniques described below can be implemented.
[0038] A user 202 can interact with the search system 214 through a
user device 204. For example, the user device 204 can be a computer
coupled to the search system 214 through a data communication
network 212, e.g., local area network (LAN) or wide area network
(WAN), e.g., the Internet, or a combination of networks. In some
cases, the search system 214 can be implemented on the user device
204, for example, if a user installs an application that performs
searches on the user device 204. The user device 204 will generally
include a memory, e.g., a random access memory (RAM) 206, for
storing instructions and data and a processor 208 for executing
stored instructions. The memory can include both read only and
writable memory.
[0039] A user 202 can use the user device 204 to submit a query 210
to a search system 214. A search engine 230 within the search
system 214 performs a search to identify resources matching the
query. When the user 202 submits a query 210, the query 210 may be
transmitted through the network 212 to the search system 214. The
search system 214 includes an index database 222 and the search
engine 230. The search system 214 responds to the query 210 by
generating search results 228, which are transmitted through the
network to the user device 204 for presentation to the user 202,
e.g., as a search results web page to be displayed by a web browser
running on the user device 204.
[0040] In this specification, the term "database" will be used
broadly to refer to any collection of data: the data does not need
to be structured in any particular way, or structured at all, and
it can be stored on storage devices in one or more locations. Thus,
for example, the index database 222 can include multiple
collections of data, each of which may be organized and accessed
differently. Similarly, in this specification the term "engine"
will be used broadly to refer to a software based system or
subsystem that can perform one or more specific functions.
Generally, an engine will be implemented as one or more software
modules or components, installed on one or more computers in one or
more locations. In some cases, one or more computers will be
dedicated to a particular engine; in other cases, multiple engines
can be installed and running on the same computer or computers.
[0041] When the query 210 is received by the search engine 230, the
search engine 230 identifies resources that satisfy the query 210.
The search engine 230 will generally include an indexing engine 220
that indexes resources, an index database 222 that stores the index
information, and a ranking engine 252 or other software that
generates scores for the resources that satisfy the query 210 and
that ranks the resources according to their respective scores.
[0042] The search system 214 also includes or can communicate with
a related entities engine 240 that determines, from the search
results 228, whether the query 210 is directed to a particular
entity, i.e., whether the query should be classified as being
directed to the particular entity. Determining whether a query is
directed to a particular entity will be described in more detail
below with reference to FIG. 4. If the query is directed to a
particular entity, the related entities engine 240 identifies
entities that have a predetermined relationship to the particular
entity. Identifying entities that have a predetermined relationship
to the particular entity will be described in more detail below
with reference to FIG. 3. Once the related entities are identified,
the search system 214 can transmit information identifying the
related entities to the user device 204 as part of a response to
the search query 210, e.g., with the search results 228 or in place
of the search results 228.
[0043] In order to determine whether the query is directed to a
particular entity and to identify the entities that are related to
the particular entity, the related entities engine 240 can
communicate with a related entities index database 250. The related
entities index database 250 includes two indices, one that maps
each entity of a group of entities to one or more related entities
and identifies a relationship between the entity and the one or
more related entities, and another that maps, to each entity of the
group of entities, one or more authoritative resources for the
entity. Building these indices is described below with reference to
FIG. 6.
[0044] FIG. 3 is a flow diagram of an example process 300 for
identifying one or more related entities to be identified as part
of a response to a search query. For convenience, the process 300
will be described as being performed by a system of one or more
computers located in one or more locations. For example, a search
system, e.g., the search system 214 of FIG. 2, appropriately
programmed, can perform the process 300.
[0045] The system receives a search query from a user device (step
302) and obtains search results for the search query from a search
engine (step 304).
[0046] The system determines that the search query is about a
principal entity (step 306). The system does so by analyzing the
search results obtained for the search query. Determining that a
search query is directed to an entity from an analysis of search
results for the search query is described in more detail below with
reference to FIG. 4.
[0047] The system determines that one or more other entities have a
relationship with the principal entity (step 308). The system
determines that the one or more other entities have a relationship
with the principal entity by accessing an index, e.g., an index in
the related entities index database 250 of FIG. 2, that maps
entities to other entities that have a pre-determined relationship
with the entity. The index also identifies the type of the one or
more related entities and, optionally, the relationship between the
entity to which the search query is directed and the related
entities. The related entities can be of the same type as the
entity or of a different type, depending on the pre-determined
relationship. For example, for a particular movie, the related
entities may be actors who starred in the movie, the producer of
the movie, the director of the movie, and so on. Alternatively, the
related entities may be other movies that were produced by the same
producer, that were directed by the same director, or that share
one or more actors with the movie. The index can also identify the
type of the related entities, e.g., "actor," and the relationship
between the related entities and the principal entity, e.g., "acted
in."
[0048] The system determines that related entities should be
identified in a response to the search query (step 310).
Determining whether related entities should be identified in a
response to a search query will be described below with reference
to FIG. 5.
[0049] The system transmits information identifying the related
entities as part of a response to the search query (step 312). The
information identifying the related entities can be, e.g., included
in a search results web page and transmitted to the user device for
presentation to a user. The information identifying the related
entities can include the name of each entity presented to the user
in the form of a link that, when selected by a user, submits a
search query derived from the name of the entity to a search
engine, e.g., the search engine 230 of FIG. 2. The search query
derived from the name of the entity can include only the name of
the related entity or the name and, e.g., one or more of the type
of the related entity and the name of the principal entity,
depending on whether the query consisting of only the name of the
entity is determined to be ambiguous.
[0050] A search query can be determined to be ambiguous if the
search results for the search query indicate that the search query
is not directed to any one particular entity. That is, if, after an
analysis of the search results for the search query, it is
determined that the search query is not directed to any entity or
is directed to more than one entity, the search query is determined
to be ambiguous. Determining that a search query is directed to an
entity from an analysis of search results for the search query is
described in more detail below with reference to FIG. 4. If the
search results are ambiguous, the link, when selected by the user,
submits a query that includes the name of the entity and one or
more of the type of the related entity and the name of the
principal entity.
[0051] The information identifying the related entities can
optionally include, instead of or in addition to the names of the
related entities, an image that corresponds to the related entity.
Like the names of the entities, each image can be presented in the
form of a link, that when selected by a user, submits a search
query derived from the name of the entity to which the image
corresponds to the search engine. The system can obtain the
corresponding image for a related entity by submitting a search
query derived from the name of the entity to an image search engine
and selecting an image from the images identified by image search
results for the search query, e.g., by selecting the image
identified by a highest-ranked image search result. The query
derived from the name of the entity can be a query that has been
determined to not be ambiguous, e.g., using the technique described
above. Further, in some implementations, the system prefers images
that have particular predetermined properties, e.g., that have an
aspect ratio that falls within a predetermined range of aspect
ratios. That is, the system can select only images having
properties that match the predetermined properties, provided that
the image search result that identifies the image has a ranking
that satisfies a predetermined threshold value or has a score that
satisfies a predetermined threshold score.
[0052] Alternatively, the system can maintain an index that
provides images for entities. The information identifying the
related entities can also optionally include metadata that is
associated with the related entities in the index. For example, for
an entity of the type "book," the metadata can identify the year
the book was originally published.
[0053] FIG. 4 is a flow diagram of an example process 400 for
determining whether a search query is directed to a particular
entity. For convenience, the process 400 will be described as being
performed by a system of one or more computers located in one or
more locations. For example, a search system, e.g., the search
system 214 of FIG. 2, appropriately programmed, can perform the
process 400.
[0054] The system obtains search results for a search query from a
search engine (step 402).
[0055] The system determines whether a sufficient number of
resources identified by the search results are authoritative
resources for a particular entity (step 404). For example, the
system may determine whether a count of resources that are
authoritative resources for the particular entity exceeds a
threshold value. In determining which resources are authoritative
resources, the system may optionally consider resources identified
by a specified number of highest-ranked search results or search
results having a score assigned to them by the search engine that
exceeds a threshold value.
[0056] The system determines whether a resource identified by a
search result is an authoritative resource for any entities by
accessing an index, e.g., an index included in the related entities
database 250 of FIG. 2, that maps authoritative resources to
entities. An authoritative resource for an entity is a resource
whose occurrence in search results has been determined to be a
strong indicator that the search query is directed to the entity.
Determining which entities are authoritative and building the index
is described below with reference to FIG. 6.
[0057] If the number of resources that are authoritative resources
for the particular entity is sufficient, the system classifies the
search query as being directed to the particular entity (step
406).
[0058] If an insufficient number of resources are authoritative
resources for the particular entity, the system classifies the
search query as not being directed to the particular entity (step
408).
[0059] FIG. 5 is a flow diagram of an example process 500 for
determining whether related entities should be identified in a
response to a particular search query. For convenience, the process
500 will be described as being performed by a system of one or more
computers located in one or more locations. For example, a search
system, e.g., the search system 214 of FIG. 2, appropriately
programmed, can perform the process 500.
[0060] The system obtains search results for a search query from a
search engine (step 502). The search query is a query that has been
determined to be directed to a particular entity that is related to
one or more entities of a particular entity type, e.g., by
performing the process described above with reference to FIG. 4.
The system also obtains data that, for at least some of the
resources identified by the search results, identifies one or more
entity types that are relevant to each of the resources. For
example, the data may identify the entity types "car" and "movie"
as being relevant to one resource identified by one search result,
the entity types "actor" and "author" as being relevant to another
resource identified by another search result, and so on.
[0061] The system determines whether more than a threshold number
of resources identified by the search results contain references to
the particular entity (step 504). In determining which resources
contain references to the particular entity, the system may
optionally consider only resources identified by a pre-determined
number of highest-ranked search results or by search results having
a score assigned to them by the search engine that exceeds a
threshold value. For example, the system can determine whether the
proportion of highest-ranking search results that include at least
one recognized reference to the particular entity, e.g., a known
name for the particular entity, in the title or the text snippet
extracted from the resource identified by the search result exceeds
a threshold value. For example, the system may determine whether
two of the top five highest-ranking search results, three of the
top ten highest-ranking search results, or thirty of the top one
hundred highest-ranking search results include a recognized
reference to the particular entity.
[0062] If an insufficient number of resources identified by the
search results contain references to the particular entity, the
system determines that related entities should not be identified in
a response to the search query (step 510).
[0063] If a sufficient number of resources identified by the search
results contain references to the particular entity, the system
determines whether the entity type of the related entities is
relevant to more than a threshold number of resources identified by
the search results (step 506) using the data about relevant entity
types obtained from the search engine. In determining which
resources have relevant entity types that match the type of the
related entities, the system may optionally consider only resources
identified by a specified number of highest-ranked search results
or search results having a score assigned to them by the search
engine that exceeds a threshold value. For example, for a search
query determined to be directed to an entity of the type "author,"
one or more entities of the type "book" may have a relationship to
the author. The system can then check whether a sufficient number
of resources identified by a predetermined number of highest-ranked
search results have a relevant entity type of "book" before
determining to return names of the books that relate to the author
as part of a response to the search query.
[0064] If a sufficient number of resources identified by the search
results have a relevant entity type that matches the type of the
related entities, the system determines that related entities
should be identified in a response to the search query (step
508).
[0065] If an insufficient number of resources identified by the
search results have a relevant entity type that matches the type of
the related entities, the system determines that related entities
should not be identified in a response to the search query (step
510).
[0066] In some implementations, the system has access to
information that characterizes the search query as either belonging
to or not belonging to one or more special classes. The system can
obtain the information from, e.g., one or more services included in
the search engine from which the search results are obtained. For
example, the system can obtain data that characterizes the search
query as potentially being one or more of pornographic,
navigational, or local, or that characterizes the search query as a
query that is seeking a particular item of information. In such
implementations, even if the other criteria for identifying related
entities in a response to the search query are satisfied, the
system can refrain from returning information about related
entities as part of a response to the search query if the
information indicates that the search query belongs to one or more
of the special cases, e.g., because returning names of related
entities could either be inappropriate or undesirable to the
user.
[0067] FIG. 6 is a flow diagram of an example process 600 for
building indices to be used in selecting relevant entities. For
convenience, the process 600 will be described as being performed
by a system of one or more computers located in one or more
locations. For example, a search system, e.g., the search system
214 of FIG. 2, appropriately programmed, can perform the process
600.
[0068] The process 600 can be performed for multiple entities of
multiple types.
[0069] The system obtains data identifying a particular entity of a
particular type (step 602). The obtained data includes one or more
names for the particular entity and identifies the type of the
entity. The obtained data can also optionally identify one or more
resources associated with the entity. For example, for the author
J. R. R. Tolkien, the obtained data can include the name of the
entity, "J. R. R Tolkien," and identify the type of the entity,
"author." The data can also optionally include the resource
locators for one or more resources associated with the author J. R.
R. Tolkien, e.g., an online encyclopedia page directed to the
author or an official webpage of the author. In some circumstances,
the obtained data may identify more than one type for the
particular entity. For example, the data could characterize Will
Smith as being of the type "actor" and of the type "musician."
[0070] The system can obtain data identifying entities from a
variety of sources. For example, one source may be an online
database of structured data that includes nodes that represent
entities and identifies the type of each entity represented by a
node. An example of an online database of structured data that
exists is the FREEBASE database that is accessible on the Internet
at http://www.freebase.com. Other sources can include online
encyclopedias having pages directed to each of a group of entities
and websites directed to particular types of entities, e.g., a
website that includes resources directed to movies and
movie-related entities, e.g., actors, directors, and producers.
[0071] The system identifies one or more resources as authoritative
resources for the particular entity (step 604). If the obtained
data identifying the entity also identifies resources associated
with the entity, the system can select those resources as
authoritative resources for the entity. For example, an online
encyclopedia page for an entity may contain links to other
resources that relate to the entity, e.g., the official website of
the entity. Additionally, resources relating to the entity may be
associated with the node representing a particular entity in an
online database of structured data, e.g., by way of a link to
another node or by way of a link representing a property of the
entity.
[0072] If the data does not identify any associated resources for
an entity, or to augment the resources identified for the entity by
the data, the system can submit a search query derived from the
name or names of the entity to a search engine and obtain search
results for the search query. The system can then select as
authoritative resources for the entity particular resources from
the resources identified by the obtained search results. For
example, the system can select a specified number of
highest-scoring search results or each search result having a score
that exceeds a threshold score.
[0073] The system associates the authoritative resources with the
particular entity in an index (step 606). For example, for each
authoritative resource for a particular entity, the system can
generate a mapping from, i.e., data defining an association
between, the resource locator of the resource to the particular
entity. The index can be, e.g., one of the indices included in the
related entities index database 250.
[0074] If the obtained data identifies more than one entity type
for the particular entity, the system can select one of the types
as the entity type for the entry for the particular entity in the
index. For example, the system can obtain search results for a
search query that is derived from the name of the particular
entity. For each of a pre-determined number of highest-ranked
search results, the system can obtain data identifying the relevant
entity types for the resource identified by the search result,
e.g., from a service that identifies the entity types that are
relevant to resources. The system can then select one of the entity
types for the particular entity based on the relevant entity types,
e.g., select the entity type that is relevant to the most resources
as the entity type for the particular entity.
[0075] Alternatively, the system can generate an entry in the index
for each of the types for that entity, e.g., one entry for Will
Smith the "actor" and one for Will Smith the "musician," and
associate one or more of the identified authoritative resources
with the respective entry for each of the types. The system can
select which of the authoritative resources are associated with
each of the entries for the particular entity by obtaining data
that, for each of the authoritative resources, identifies the
relevant entity types for that authoritative resource. For each of
the index entries for the particular entity, the system can then
associate the authoritative resources having a related entity type
that matches the entity type for that entry.
[0076] For example, in the case where Will Smith is identified as
both an "actor" and a "musician," the system may identify two
authoritative resources for Will Smith: a web page directed to Will
Smith from a web site about actors and movies and a web page
directed to Will Smith from a social media web site for musicians.
The system can obtain data identifying the most relevant entity
types for each of the authoritative resources and associate the
page from the web site about actors and movies with entity "Will
Smith" having the type "actor", e.g., because the obtained data
indicated that the entity type "actor" is relevant to the page. The
system can also associate the page from the social media web site
with the entity "Will Smith" having the entity type "musician",
e.g., because the obtained data indicated that the entity type
"musician" is relevant to the page.
[0077] The system obtains data identifying other entities having a
relationship with the particular entity (step 608). If the
particular entity has more than one type, the system obtains data
identifying other entities for each of the types. The desired type
of relationship can be predetermined, e.g., specified by a system
administrator. That is, the system administrator can specify that,
for entities of the type "author," the obtained data should
identify entities of the type "book" that were written by the
author.
[0078] The system can obtain the data identifying the other
entities and their relationship with the entity from, e.g., the
same source from which the data identifying the entity was obtained
or from additional sources. For example, the system can query the
online database of structured data to obtain data identifying
entities that relate to the entity. For example, for an entity
representing an actor, the system can query the online database of
structured data to obtain data identifying one or more movies in
which the actor acted. Additionally, a page in an online
encyclopedia directed to the entity may identify other entities
that relate to the entity. For example, an online encyclopedia page
for a musical artist can identify albums by the musical artist,
popular songs of the musical artist, and so on.
[0079] The system orders the entities having a predetermined
relationship with the particular entity (step 610). In some
implementations, the system orders the related entities according
to the order in which they were received by the system from a data
source. However, in other implementations, the system reorders the
related entities, e.g., to account for users submitting search
queries that are directed to the particular entity being more
interested in information about particular ones of the entities
that are related to the particular entity. Ordering related
entities is described below with reference to FIG. 7.
[0080] The system associates the related entities with the
particular entity in an index (step 612). For example, the system
can generate a mapping from the particular entity to each of the
related entities. The mapping can also identify the type of the
related entities and, optionally, the nature of the relationship
between the particular entity and the related entities. The index
can be, e.g., one of the indices included in the related entities
index database 250. The system can generate the mapping in such a
manner that, when the related entities are selected for
presentation to a user in response to a search query directed to
the particular entity, the related entities are presented in an
order that matches the order generated by the system.
[0081] In some implementations, the system also obtains additional
information about each of the related entities from one of the data
sources and stores the additional information in an index, e.g., as
metadata associated with the related entity, for later display to a
user, e.g., as described above with reference to FIG. 1. The data
obtained may depend on the type of the related entities and on the
relationship between the related entities and the particular
entity. For example, if the particular entity is an entity of the
type "movie" and the related entities are entities of the type
"actor" that acted in the movie, the additional information may
include the name of the character played by each of the related
entities. However, if the particular entity is an entity of the
type "author" and the related entities are entities of the type
"book" that are written by the author, the additional information
may include the year that each of the related entities was first
published. Thus, the additional information may be a value of a
property that the related entity possesses by virtue of that
entity's relationship with the particular entity.
[0082] FIG. 7 is a flow diagram of an example process 700 for
ordering related entities. For convenience, the process 700 will be
described as being performed by a system of one or more computers
located in one or more locations. For example, a search system,
e.g., the search system 214 of FIG. 2, appropriately programmed,
can perform the process 500.
[0083] The system obtains data identifying related entities for a
particular entity (step 702).
[0084] The system determines a ranking score for each of the
related entities (step 704). The system determines the ranking
scores by aggregating two or more of a variety of factor-specific
scores, with each factor-specific score being computed based on a
respective factor.
[0085] For example, the system may generate a score for each of the
related entities based on how frequently a recognized reference to
each related entity, e.g., a known name of the related entity,
co-occurs with a recognized reference to the particular entity in
resources indexed by an indexing engine, e.g., the indexing engine
220 of FIG. 2, e.g., so that related entities that co-occur more
frequently with the particular entity have higher scores than
related entities that co-occur less frequently with the particular
entity.
[0086] As another example, the system may generate a score for each
of the related entities based on how frequently each related entity
is searched for by users after submitting a query directed to the
particular entity. For example, the system may obtain data that
identifies, for each of the related entities, how frequently users
submit search queries that include a recognized reference to the
related entity after submitting an initial search query that
includes a recognized reference to the particular entity, e.g.,
immediately following submitting the initial search query. A later
search query can be considered to be submitted immediately
following an earlier search query if it is submitted within a
pre-determined window of time of submitting the earlier search
query and if, when the later search query is submitted, no
additional search queries have been submitted by the user after the
earlier search query was submitted. The system can generate the
scores so that related entities that are searched for more
frequently after submitting a query directed to the particular
entity have higher scores than related entities that are searched
for less frequently after submitting a query directed to the
particular entity.
[0087] As another example, the system may generate a score for each
of the related entities based on the global popularity of each of
the related entities. The global popularity of a related entity can
be measured based on how frequently a recognized reference to the
related entity appears in resources indexed by the indexing engine,
how frequently a recognized reference to the related entity appears
in previously submitted search queries, i.e., search queries stored
in a record of queries that have been submitted to a search engine
by users, or both. Alternatively, the global popularity of a
related entity can be based at least in part on how frequently
authoritative resources for the related entity are identified in
search results for previously submitted queries. For example, the
global popularity may be based at least in part on the number of
previously submitted queries for which an authoritative resource
for the related entity is identified by one of a pre-determined
number of highest-ranked search results. The system can generate
the scores so that a related entity that has a higher global
popularity than another entity will have a higher score than a
related entity that has a lower global popularity.
[0088] As another example, the system may generate a score for each
of the related entities based on how frequently a recognized
reference to the related entity co-occurs in the same previously
submitted search query as a recognized reference to the particular
entity, e.g., so that related entities that co-occur more
frequently with the particular entity in previously submitted
search queries have higher scores than related entities that
co-occur less frequently with the particular entity.
[0089] The system can then generate a ranking score for each
related entity based on the factor-specific scores for the entity.
The system can generate the ranking score for a given entity by,
e.g., normalizing the factor-specific scores for the entity and
then computing an average of the normalized scores, computing a sum
of the normalized scores, computing a product of the normalized
scores, or otherwise aggregating the normalized scores.
[0090] The system orders the related entities according to their
ranking scores (step 706). In some implementations, the system can
make further adjustments to the ordering of the related entities
after ordering the entities according to their ranking scores. In
particular, the system may have access to data that specifies an
ordering for one or more sets of entities. For example, the data
may specify that movies in a particular movie trilogy be ordered by
their release date or that Presidents of the United States be
ordered by the date their term began or ended. If the data
indicates two or more of the related entities are members of a set
of entities that has a specified order, the system can adjust the
order of the members of the set to match the specified order. In
some implementations, if the members of the set of entities are
separated by other entities in the order of related entities, the
system reorders the members of the set to match the specified order
and places the reordered members of the set together in the order
of related entities, e.g., beginning at the position of the
highest-ranked entity in the set or at the average position of the
entities in the set. In some other implementations, if the members
of the set of entities are separated by other entities in the order
of related entities the system refrains from adjusting the order of
the members of the set to match the specified order.
[0091] As another example, the system may have access to data that
identifies sets of entities that are better known as being part of
a broader entity. For example, the data may indicate that the
individual books that make up a popular book series are better
known as being part of the series rather than as individual books.
If the data indicates that some or all of the related entities are
included in a broader entity, the system can replace those related
entities in the order with the broader entity. For example, the
related entities for an author may include books written by that
author. If the author has written a well-known trilogy of books and
those books are included in the related entities for the author,
the system may replace the books in that trilogy with a single
entity that represents the trilogy. In some implementations, if the
entities in the set of entities that is better known as being part
of a broader entity are separated by other entities in the order of
the related entities, the system places the broader entity in the
order at the position of the highest-ranking entity in the set.
Alternatively, the system can place the broader entity in the order
at a position that is an average of the positions of the entities
in the set. In some other implementations, the system can refrain
from replacing the entities in the set with the broader entity if
the entities in the set are separated by other entities in the
order of the related entities.
[0092] While the processes 600 and 700 describe obtaining data that
identifies entities that relate to the particular entity and then
ordering the related entities, in some circumstances, e.g., when
the related entities are of the same type as the particular entity,
the system may refine candidate entities identified by the obtained
data in order to identify the entities that relate to the
particular entity. For example, for a particular entity of the type
"person," the system may obtain data identifying a large number of
other entities of the type "person" that are represented by nodes
in the online database of structured data. The system can then
refine the obtained entities in order to identify the entities of
the type "person" that relate to the particular entity.
[0093] FIG. 8 is a flow diagram of an example process 800 for
mapping an entity to related entities of the same type. For
convenience, the process 800 will be described as being performed
by a system of one or more computers located in one or more
locations. For example, a search system, e.g., search system 214 of
FIG. 2, appropriately programmed, can perform the process 800.
[0094] The process 800 can be performed for multiple entities of
multiple types. For example, the process 800 may be performed for
each type for which, in response to a search query that is about a
given entity of the type, it is desirable to return information
identifying other entities of the type that are related to the
given entity, e.g., because users often submit additional search
queries referencing other entities of the type after submitting an
initial query referencing an entity of the type.
[0095] The system obtains data identifying a particular entity of a
particular type (step 802). The obtained data includes one or more
names for the particular entity and identifies the type of the
entity. The system can obtain the data, e.g., from the online
database of structured data.
[0096] The system identifies other entities of the particular type
that are related to the particular entity (step 804). For example,
the system can query the online database of structured data to
obtain data identifying other entities of the particular type. The
system can then identify the entities of the particular type that
are related to the particular entity based on how frequently a
recognized reference to each other entity co-occurs with a
recognized reference to the particular entity in resources indexed
by an indexing engine, e.g., indexing engine 220 of FIG. 2. For
example, the system can select as related entities a predetermined
number of other entities that co-occur most frequently with the
particular entity. Alternatively, the system can select as related
entities those other entities that co-occur with the particular
entity at a frequency that exceeds a threshold frequency.
[0097] The system orders the related entities (step 806). The
system may calculate a co-occurrence score for each related entity
based on how frequently a recognized reference to each related
entity co-occurs with a recognized reference to the particular
entity in resources indexed by the indexing engine, e.g., so that
related entities that co-occur more frequently with the particular
entity have a higher co-occurrence score than related entities that
co-occur less frequently with the particular entity.
[0098] The system may also calculate a subsequent query score for
each related entity based on how frequently each related entity is
searched for by users after submitting a search query directed to
the particular entity. For example, the system may obtain data that
identifies, for each of the related entities, how frequently users
submit search queries that include a name of the related entity
after submitting an initial search query that includes a name of
the particular entity, e.g., within a pre-determined window of time
of submitting the initial search query or immediately following
submitting the initial search query. The system can then calculate
the subsequent query scores, e.g., so that entities that are
searched for more frequently after the initial search query is
submitted have higher subsequent query scores than related entities
that are searched for less frequently after the initial search
query is submitted.
[0099] The system can then generate a ranking score for each
related entity based on the co-occurrence score, the subsequent
query score, or both and order the related entities in accordance
with the ranking scores. The system can generate the ranking score
for a given entity by, e.g., normalizing the co-occurrence score
and the subsequent query score for the entity and then computing an
average of the normalized scores, computing a sum of the normalized
scores, computing a product of the normalized scores, or otherwise
aggregating the normalized scores.
[0100] The system associates the related entities with the
particular entity in an index (step 808). For example, the system
can generate a mapping from the particular entity to each of the
related entities. The mapping can also identify the type of the
related entities and, optionally, the nature of the relationship
between the particular entity and the related entities. The index
can be, e.g., one of the indices included in the related entities
index database 250. The system can generate the mapping in such a
manner that, when the related entities are selected for
presentation to a user in response to a search query directed to
the particular entity, the related entities are presented in an
order that matches the order generated by the system.
[0101] In some implementations, before associating the related
entities of the particular type with the particular entity, the
system determines whether, for each related entity, both the
co-occurrence score and the subsequent query score for the related
entity exceed respective threshold values. If, for a given related
entity, either score does not exceed the threshold value, the
system can refrain from associating the related entity with the
particular entity in the index.
[0102] Additionally, in some implementations, the system determines
whether sufficient data exists for the particular entity before
associating any related entities of the particular type with the
particular entity. For example, the system can determine whether a
recognized reference to the entity occurs in more than a threshold
number of search queries or in more than a threshold number of
resources. If insufficient data exists for the particular entity,
the system can determine not to associate any related entities of
the particular type with the entity in the index.
[0103] Embodiments of the subject matter and the functional
operations described in this specification can be implemented in
digital electronic circuitry, in tangibly-embodied computer
software or firmware, in computer hardware, including the
structures disclosed in this specification and their structural
equivalents, or in combinations of one or more of them. Embodiments
of the subject matter described in this specification can be
implemented as one or more computer programs, i.e., one or more
modules of computer program instructions encoded on a tangible
non-transitory program carrier for execution by, or to control the
operation of, data processing apparatus. Alternatively or in
addition, the program instructions can be encoded on an
artificially-generated propagated signal, e.g., a machine-generated
electrical, optical, or electromagnetic signal, that is generated
to encode information for transmission to suitable receiver
apparatus for execution by a data processing apparatus. The
computer storage medium can be a machine-readable storage device, a
machine-readable storage substrate, a random or serial access
memory device, or a combination of one or more of them.
[0104] The term "data processing apparatus" refers to data
processing hardware and encompasses all kinds of apparatus,
devices, and machines for processing data, including by way of
example a programmable processor, a computer, or multiple
processors or computers. The apparatus can also be or further
include special purpose logic circuitry, e.g., an FPGA (field
programmable gate array) or an ASIC (application-specific
integrated circuit). The apparatus can optionally include, in
addition to hardware, code that creates an execution environment
for computer programs, e.g., code that constitutes processor
firmware, a protocol stack, a database management system, an
operating system, or a combination of one or more of them.
[0105] A computer program (which may also be referred to or
described as a program, software, a software application, a module,
a software module, a script, or code) can be written in any form of
programming language, including compiled or interpreted languages,
or declarative or procedural languages, and it can be deployed in
any form, including as a stand-alone program or as a module,
component, subroutine, or other unit suitable for use in a
computing environment. A computer program may, but need not,
correspond to a file in a file system. A program can be stored in a
portion of a file that holds other programs or data, e.g., one or
more scripts stored in a markup language document, in a single file
dedicated to the program in question, or in multiple coordinated
files, e.g., files that store one or more modules, sub-programs, or
portions of code. A computer program can be deployed to be executed
on one computer or on multiple computers that are located at one
site or distributed across multiple sites and interconnected by a
communication network.
[0106] The processes and logic flows described in this
specification can be performed by one or more programmable
computers executing one or more computer programs to perform
functions by operating on input data and generating output. The
processes and logic flows can also be performed by, and apparatus
can also be implemented as, special purpose logic circuitry, e.g.,
an FPGA (field programmable gate array) or an ASIC
(application-specific integrated circuit).
[0107] Computers suitable for the execution of a computer program
include, by way of example, can be based on general or special
purpose microprocessors or both, or any other kind of central
processing unit. Generally, a central processing unit will receive
instructions and data from a read-only memory or a random access
memory or both. The essential elements of a computer are a central
processing unit for performing or executing instructions and one or
more memory devices for storing instructions and data. Generally, a
computer will also include, or be operatively coupled to receive
data from or transfer data to, or both, one or more mass storage
devices for storing data, e.g., magnetic, magneto-optical disks, or
optical disks. However, a computer need not have such devices.
Moreover, a computer can be embedded in another device, e.g., a
mobile telephone, a personal digital assistant (PDA), a mobile
audio or video player, a game console, a Global Positioning System
(GPS) receiver, or a portable storage device, e.g., a universal
serial bus (USB) flash drive, to name just a few.
[0108] Computer-readable media suitable for storing computer
program instructions and data include all forms of non-volatile
memory, media and memory devices, including by way of example
semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory
devices; magnetic disks, e.g., internal hard disks or removable
disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The
processor and the memory can be supplemented by, or incorporated
in, special purpose logic circuitry.
[0109] To provide for interaction with a user, embodiments of the
subject matter described in this specification can be implemented
on a computer having a display device, e.g., a CRT (cathode ray
tube) or LCD (liquid crystal display) monitor, for displaying
information to the user and a keyboard and a pointing device, e.g.,
a mouse or a trackball, by which the user can provide input to the
computer. Other kinds of devices can be used to provide for
interaction with a user as well; for example, feedback provided to
the user can be any form of sensory feedback, e.g., visual
feedback, auditory feedback, or tactile feedback; and input from
the user can be received in any form, including acoustic, speech,
or tactile input. In addition, a computer can interact with a user
by sending documents to and receiving documents from a device that
is used by the user; for example, by sending web pages to a web
browser on a user's device in response to requests received from
the web browser.
[0110] Embodiments of the subject matter described in this
specification can be implemented in a computing system that
includes a back-end component, e.g., as a data server, or that
includes a middleware component, e.g., an application server, or
that includes a front-end component, e.g., a client computer having
a graphical user interface or a Web browser through which a user
can interact with an implementation of the subject matter described
in this specification, or any combination of one or more such
back-end, middleware, or front-end components. The components of
the system can be interconnected by any form or medium of digital
data communication, e.g., a communication network. Examples of
communication networks include a local area network ("LAN") and a
wide area network ("WAN"), e.g., the Internet.
[0111] The computing system can include clients and servers. A
client and server are generally remote from each other and
typically interact through a communication network. The
relationship of client and server arises by virtue of computer
programs running on the respective computers and having a
client-server relationship to each other.
[0112] While this specification contains many specific
implementation details, these should not be construed as
limitations on the scope of any invention or of what may be
claimed, but rather as descriptions of features that may be
specific to particular embodiments of particular inventions.
Certain features that are described in this specification in the
context of separate embodiments can also be implemented in
combination in a single embodiment. Conversely, various features
that are described in the context of a single embodiment can also
be implemented in multiple embodiments separately or in any
suitable subcombination. Moreover, although features may be
described above as acting in certain combinations and even
initially claimed as such, one or more features from a claimed
combination can in some cases be excised from the combination, and
the claimed combination may be directed to a subcombination or
variation of a subcombination.
[0113] Similarly, while operations are depicted in the drawings in
a particular order, this should not be understood as requiring that
such operations be performed in the particular order shown or in
sequential order, or that all illustrated operations be performed,
to achieve desirable results. In certain circumstances,
multitasking and parallel processing may be advantageous. Moreover,
the separation of various system modules and components in the
embodiments described above should not be understood as requiring
such separation in all embodiments, and it should be understood
that the described program components and systems can generally be
integrated together in a single software product or packaged into
multiple software products.
[0114] Particular embodiments of the subject matter have been
described. Other embodiments are within the scope of the following
claims. For example, the actions recited in the claims can be
performed in a different order and still achieve desirable results.
As one example, the processes depicted in the accompanying figures
do not necessarily require the particular order shown, or
sequential order, to achieve desirable results. In certain
implementations, multitasking and parallel processing may be
advantageous.
* * * * *
References