U.S. patent application number 15/144670 was filed with the patent office on 2016-11-10 for generating content for topics based on user demand.
The applicant listed for this patent is BloomReach Inc.. Invention is credited to Raj K. De Datta, Ashutosh Garg, Anindo Mukherjee, Devesh Senapati.
Application Number | 20160328483 15/144670 |
Document ID | / |
Family ID | 51588275 |
Filed Date | 2016-11-10 |
United States Patent
Application |
20160328483 |
Kind Code |
A1 |
Mukherjee; Anindo ; et
al. |
November 10, 2016 |
GENERATING CONTENT FOR TOPICS BASED ON USER DEMAND
Abstract
Techniques for generating content for topics based on user
demand are disclosed. In some embodiments, generating content for
topics based on user demand includes determining a topic based on a
user demand; automatically generating content for the topic; and
selecting the content that is contextually relevant for display
within a corpus of content (e.g., a web site, a social networking
web page, content customized for mobile devices, content customized
based on location awareness, or an electronic mail message).
Inventors: |
Mukherjee; Anindo; (Fremont,
CA) ; Garg; Ashutosh; (Sunnyvale, CA) ; De
Datta; Raj K.; (Palo Alto, CA) ; Senapati;
Devesh; (Menlo Park, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
BloomReach Inc. |
Mountain View |
CA |
US |
|
|
Family ID: |
51588275 |
Appl. No.: |
15/144670 |
Filed: |
May 2, 2016 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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14472233 |
Aug 28, 2014 |
9361385 |
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15144670 |
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13222860 |
Aug 31, 2011 |
8849812 |
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14472233 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06F 16/958 20190101;
G06F 16/9535 20190101; G06Q 30/02 20130101 |
International
Class: |
G06F 17/30 20060101
G06F017/30 |
Claims
1. (canceled)
2. A system, comprising: a processor configured to: analyze user
behavior to determine a plurality of topics based on user demand,
wherein analyzing user behavior includes analyzing one or more of
the following: user search history, user purchase history, user
device preference, user presentation preferences, content generated
using pixel log related data, user reviews, social networking
related data, and visited information; select a topic included in
the plurality of topics for a web site based on the user demand,
wherein the web site includes a corpus of content; determine that
the web site does not include existing content for the topic in the
corpus of content; and automatically generate a landing page for
the topic, wherein the landing page includes content that is
configured or organized differently than on other web pages of the
web site; and a memory coupled to the processor and configured to
provide the processor with instructions.
3. The system recited in claim 2, wherein the landing page includes
personalized content that is based on a source of a user.
4. The system recited in claim 2, wherein the landing page includes
personalized content that is optimized for a referring source of a
user and a display device type associated with the user.
5. The system recited in claim 2, wherein the landing page includes
personalized content for a user that does not exist on the other
web pages of the web site.
6. The system recited in claim 2, wherein the processor is further
configured to: automatically add a link to the landing page to the
web site, wherein the link is crawlable by a web crawler.
7. The system recited in claim 2, wherein analyzing user behavior
to determine the plurality of topics based on user demand further
comprises: determine at least one theme based on common phrases in
a search query log from the web site, a search query log from a
search engine, or a combination thereof; cluster the at least one
theme; and determine at least one of the plurality of topics based
on the clustered at least one theme.
8. The system recited in claim 2, wherein a plurality of landing
pages are generated for the plurality of topics, and wherein the
processor is further configured to: determine performance metrics
associated with each of the plurality of landing pages.
9. The system recited in claim 2, wherein a plurality of landing
pages are generated for the plurality of topics, and wherein the
processor is further configured to: display performance metrics
associated with each of the plurality of landing pages, and wherein
each of the plurality of landing pages can be configured or
automatically removed based on the performance metrics.
10. The system recited in claim 2, wherein a plurality of landing
pages are generated for the plurality of topics, and wherein the
processor is further configured to: determine performance metrics
associated with each of the plurality of landing pages; and
automatically modify one or more of the plurality of landing pages
based on the performance metrics.
11. The system recited in claim 2, wherein a plurality of landing
pages are generated for the plurality of topics, and wherein the
processor is further configured to: determine performance metrics
associated with each of the plurality of landing pages; and
determine a charge for using each of the plurality of landing pages
based on the performance metrics associated with each of the
plurality of landing pages.
12. A method, comprising: analyzing user behavior to determine a
plurality of topics based on user demand, wherein analyzing user
behavior includes analyzing one or more of the following: user
search history, user purchase history, user device preference, user
presentation preferences, content generated using pixel log related
data, user reviews, social networking related data, and visited
information; selecting a topic included in the plurality of topics
for a web site based on the user demand, wherein the web site
includes a corpus of content; determining that the web site does
not include existing content for the topic in the corpus of
content; and automatically generating a landing page for the topic,
wherein the landing page includes content that is configured or
organized differently than on other web pages of the web site.
13. The method of claim 12, wherein the landing page includes
personalized content that is based on a source of a user.
14. The method of claim 12, wherein the landing page includes
personalized content that is optimized for a referring source of a
user and a display device type associated with the user.
15. The method of claim 12, wherein the landing page includes
personalized content for a user that does not exist on the other
web pages of the web site.
16. The method of claim 12, further comprising: automatically add a
link to the landing page to the web site, wherein the link is
crawlable by a web crawler.
17. The method of claim 12, wherein analyzing user behavior to
determine the plurality of topics based on user demand further
comprises: determining at least one theme based on common phrases
in a search query log from the web site, a search query log from a
search engine, or a combination thereof; clustering the at least
one theme; and determining at least one of the plurality of topics
based on the clustered at least one theme.
18. The method of claim 12, wherein a plurality of landing pages
are generated for the plurality of topics, and further comprising:
determining performance metrics associated with each of the
plurality of landing pages.
19. The method of claim 12, wherein a plurality of landing pages
are generated for the plurality of topics, and further comprising:
displaying performance metrics associated with each of the
plurality of landing pages, and wherein each of the plurality of
landing pages can be configured or automatically removed based on
the performance metrics.
20. The method of claim 12, wherein a plurality of landing pages
are generated for the plurality of topics, and further comprising:
determining performance metrics associated with each of the
plurality of landing pages; and automatically modifying one or more
of the plurality of landing pages based on the performance
metrics.
21. The method of claim 12, wherein a plurality of landing pages
are generated for the plurality of topics, and further comprising:
determining performance metrics associated with each of the
plurality of landing pages; and determining a charge for using each
of the plurality of landing pages based on the performance metrics
associated with each of the plurality of landing pages.
22. A system, comprising: a processor of a third party server for a
theme content service configured to: generate a theme landing page
for a topic, wherein content of the theme landing page is
configured or organized differently than on other web pages of a
web site; receive a request for the theme landing page for the
topic from a web server for the web site in response to the web
server receiving a user request for the topic at the web server,
wherein the topic is indicated as a linked topic on a web page of
the web site; and send the theme landing page for the topic to the
web server in response to the request for the theme landing page
for the topic from the web server; wherein a source of the theme
landing page for the topic is transparent to a web crawler; and a
memory coupled to the processor and configured to provide the
processor with instructions.
23. The system recited in claim 22, wherein the request for the
theme landing page for the topic from the web server is
communicated to the third party server for the theme content
service using an application programming interface.
Description
CROSS REFERENCE TO OTHER APPLICATIONS
[0001] This application is a continuation of co-pending U.S. patent
application Ser. No. 14/472,233, entitled GENERATING CONTENT FOR
TOPICS BASED ON USER DEMAND, filed Aug. 28, 2014, which is a
continuation of U.S. patent application Ser. No. 13/222,860, now
U.S. Pat. No. 8,849,812, entitled GENERATING CONTENT FOR TOPICS
BASED ON USER DEMAND, filed Aug. 31, 2011, both of which are
incorporated herein by reference for all purposes.
BACKGROUND OF THE INVENTION
[0002] Search engines (e.g., web based search engines provided by
various vendors, including, for example, Google, Microsoft's Bing,
and Yahoo) provide for searches of online information that includes
searchable content (e.g., digitally stored electronic data), such
as searchable content available via the World Wide Web (WWW). As
input, a search engine typically receives a search query (e.g.,
query input including one or more terms, such as keywords, by a
user of the search engine). The search engine performs the search
for the search query and outputs results that are typically
presented in a ranked list, often referred to as search results or
hits (e.g., links or Uniform Resource Locators (URLs) for one or
more web pages and/or web sites). The search results can include
web pages, images, audio, video, database results, directory
results, information and other types of data.
[0003] Search engines typically provide paid search results (e.g.,
the first three results in the main listing and/or results often
presented in a separate listing on the right side of the output
screen). For example, advertisers may pay for placement in such
paid search results based on keywords (e.g., keywords in search
queries). Search engines also typically provide organic search
results, also referred to as natural search results. Organic search
results are based on various algorithms employed by different
search engines that attempt to provide relevant search results
based on a received search query.
[0004] For improved Internet marketing, search engine optimization
(SEO) has developed as a form of industry/technical consulting
(often referred to as search engine optimizers) provided to web
site operators (e.g., vendors of products/services with web sites
and/or e-commerce vendors of products/services) for improving the
volume or quality of traffic to a web site from a search engine via
organic search results (e.g., to improve the web site's web
presence as a paid service engagement or pursuant to a marketing
campaign). Generally, the higher a web site appears in the organic
search results list, the more users it will receive from the search
engine. SEO can target different kinds of search, including image
search, local search, and industry specific, vertical search
engines to improve the web site's web presence. For example, SEO
often considers how search engines work and what people search for
to recommend web site related changes to optimize a web site (e.g.,
which primarily involves editing its content and HyperText Markup
Language (HTML) coding to both increase its relevance to specific
keywords and to remove barriers to the indexing activities of
search engines).
BRIEF DESCRIPTION OF THE DRAWINGS
[0005] Various embodiments of the invention are disclosed in the
following detailed description and the accompanying drawings.
[0006] FIG. 1 is a functional diagram illustrating a programmed
computer system for generating content for topics based on user
demand in accordance with some embodiments.
[0007] FIG. 2 is a functional diagram illustrating network based
search in accordance with some embodiments.
[0008] FIG. 3 is a flow diagram for generating content for topics
based on user demand in accordance with some embodiments.
[0009] FIG. 4 is another flow diagram for generating content for
topics based on user demand in accordance with some
embodiments.
[0010] FIG. 5 is another flow diagram for generating content for
topics based on user demand in accordance with some
embodiments.
[0011] FIG. 6 is another flow diagram for generating content for
topics based on user demand in accordance with some
embodiments.
[0012] FIG. 7 is a functional diagram illustrating a web page
including links to topics based on user demand in accordance with
some embodiments.
[0013] FIG. 8 is a network architecture for generating content for
topics based on user demand in accordance with some
embodiments.
[0014] FIG. 9 is another flow diagram for generating content for
topics based on user demand in accordance with some
embodiments.
DETAILED DESCRIPTION
[0015] The invention can be implemented in numerous ways, including
as a process; an apparatus; a system; a composition of matter; a
computer program product embodied on a computer readable storage
medium; and/or a processor, such as a processor configured to
execute instructions stored on and/or provided by a memory coupled
to the processor. In this specification, these implementations, or
any other form that the invention may take, may be referred to as
techniques. In general, the order of the steps of disclosed
processes may be altered within the scope of the invention. Unless
stated otherwise, a component such as a processor or a memory
described as being configured to perform a task may be implemented
as a general component that is temporarily configured to perform
the task at a given time or a specific component that is
manufactured to perform the task. As used herein, the term
`processor` refers to one or more devices, circuits, and/or
processing cores configured to process data, such as computer
program instructions.
[0016] A detailed description of one or more embodiments of the
invention is provided below along with accompanying figures that
illustrate the principles of the invention. The invention is
described in connection with such embodiments, but the invention is
not limited to any embodiment. The scope of the invention is
limited only by the claims and the invention encompasses numerous
alternatives, modifications and equivalents. Numerous specific
details are set forth in the following description in order to
provide a thorough understanding of the invention. These details
are provided for the purpose of example and the invention may be
practiced according to the claims without some or all of these
specific details. For the purpose of clarity, technical material
that is known in the technical fields related to the invention has
not been described in detail so that the invention is not
unnecessarily obscured.
[0017] A web site typically includes of a set of interconnected web
pages. A web page generally includes content of any of a variety of
different types. The content of a web page can include content that
is searchable, for example, by a search engine. The content of a
web page can also include one or more hyperlinks that provide
navigation to other web pages and/or resources. The structure of a
web site is generally defined by the hierarchical organization of
web pages including the web site as well as the links existing
between pages of the web site. It may be desirable to enhance the
content and/or structure of a web site, for example, to improve the
discoverability of the web site (e.g., for user query/navigation
and/or search engine crawling and web page rankings for various
queries) and to provide web pages with more relevant
information.
[0018] Numerous factors can affect the discoverability of a web
site and its associated web pages. In some cases, key content
associated with a page may not be searchable. At least some of the
content of a page may be dynamically generated and provided with a
page (e.g., via a JavaScript widget), in response to a user request
for the page. For example, some of the dynamic content of a page
can be generated client-side (e.g., by a web browser executed on a
client device, that is, a user's device). Although dynamic content
may be relevant to searches, it is typically not crawlable by
search engines. Server-side static content associated with a page
may be searchable, but many issues may also arise with respect to
the searchable content of a page. For example, the discoverability
of the content of a page may be affected by language usage,
especially if important content of the page fails to encompass
variations that may instead be used to search for or otherwise
locate the content. For example, the content of a page may not
include all or at least a relevant subset of synonyms of important
keywords, terms, or phrases (e.g., table vs. desk); colloquial
variations (e.g., cell phone vs. mobile phone); spelling variations
(e.g., Hanukkah vs. Chanukah); geographical variations (e.g.,
Silicon Valley vs. Bay Area); categorical variations (e.g., a
clothing merchandise web site that does not categorize men's dress
shirts by pattern, such as plaid or pin-striped), and/or various
other categorical, ontological, localization, language or
grammatical, structural (e.g., pages may be too deep or dynamically
generated and, thus, not discoverable by users and/or search
engines), and/or other variations that render the web site content,
structure, or organization to not be optimized for certain user
queries. Moreover, content may not be presented in a manner that is
conducive to searches and/or user navigation. Furthermore, a
fragmented distribution or organization of content across the pages
comprising a web site may result in the web site content not
satisfying common search terms or queries. For example, a
restaurant web site that indicates on a home or main page that the
restaurant serves Japanese food and a San Francisco address but
that has on another page a menu that includes sushi may not be
provided or at least highly ranked as a search result in response
to a user query for "sushi San Francisco." The discoverability of a
page may also be affected by the manner in which the page is linked
to other pages. For example, a page may not be easily accessible by
a search engine or a user if it is too deeply buried or nested
within the page hierarchy of a web site.
[0019] Various techniques for adding dynamic content (e.g., via
JavaScript) to a web page exist. However, such content of a web
page is generally not crawlable or searchable and, thus, generally
cannot be used by search engines to retrieve and/or rank the web
page.
[0020] Web site owners typically rely on Search Engine Optimization
(SEO) consultants to optimize their web sites and/or associated web
pages to make them more amenable for search engine retrieval and/or
ranking. However, such SEO consultants generally provide web site
content/structural change recommendations that require that the SEO
consultants or the web site operator manually modify the content
and/or structures of web sites so that the web sites and/or
associated web pages can be better located by users and search
engines. Such manual changes are static changes based on analysis
of the web site at a particular period of time, and thus, such
manual changes cannot account for changing user demand for content
on the web site.
[0021] What is needed is content generation for topics based on
user demand. Accordingly, techniques for generating content for
topics (e.g., themes and/or sub-themes) based on user demand are
disclosed. For example, the techniques described herein can
significantly enhance the content and/or discoverability of
existing content of a web site (e.g., for an entity or for a brand)
and its associated pages as well as make the web site and its
associated pages more amenable to various third party services
(e.g., search engines) by providing richer content on pages and/or
improved navigation to pages. Although some of the given examples
are described with respect to web pages of a web site, the
techniques disclosed herein can be employed with respect to any
other organization of a corpus of content whose content is desired
to be improved to facilitate enhanced content for topics based on
user demand (e.g., web content and/or other forms of content, such
as e-mails, content for mobile devices, such as for web pages for
mobile devices or for applications for mobile devices, and/or
content customized based on location awareness). For example, a
corpus of content can include a web site, a user's social
networking web page, content customized for mobile devices, content
customized based on location awareness, an electronic mail message,
and/or any other collection of digitally stored content.
[0022] In some embodiments, content for topics, such as for themes
or related themes or sub-themes (e.g., thematic pages) facilitate a
web site capturing traffic for new category-like/torso and tail
query traffic (e.g., which are queries that can be dynamically
changing over time), through the generation and delivery of
optimized (e.g., high user-value and search-engine friendly)
landing pages that enhances, for example, a web site content and/or
structure to enable discovery of the web site's relevant content
that corresponds to such category-like/torso and tail query
traffic.
[0023] For example, a merchandise web site for clothing merchandise
can be enhanced include various new thematic pages that include
optimized content for a user's request to view merchandise
corresponding to a query for a "blue pin-striped men's dress shirt"
(e.g., even if the merchandise web site does not otherwise
categorize its dress shirt merchandise by patterns), using various
techniques described herein. As another example, a furniture web
site can be enhanced to include thematic pages for leather chair as
a theme and also include refinements or sub-themes for leather
theatre seat, leather club chair, leather ottoman, and/or various
other sub-themes or refinements, using various techniques described
herein. As yet another example, a travel web site that does not
include a static page for flights from San Francisco to New York
City can be enhanced to include a thematic page for flights from
San Francisco to New York City and/or various other travel patterns
or sub-themes related to such travel patterns (e.g., hotels in New
York City or car rentals in New York City), using various
techniques described herein.
[0024] Thus, using various techniques described herein can provide
for enhanced capture of natural language queries from users (e.g.,
queries of users at search engines and/or search queries from users
while users are navigating within the web site, such as using the
search option of the web site). Using various techniques described
herein can also provide for enhanced web site content to allow for
bidding for keywords for landing pages. Using various techniques
described herein can also improve a web site's structure and expand
the web site's content and structure, which can thereby improve
organic search results for the web pages of the web site.
[0025] In some embodiments, thematic pages (e.g., landing pages for
a given theme or topic or sub-topic or refinement) are generated
dynamically based on user demand (e.g., observed user demand over
time and/or in anticipation of user demand). For example, content
that reflect a user's behavior (e.g., based on the user's behavior
on or off the web site) and that is based on the web site's content
can be created (e.g., as needed, depending on the existing content
of the web site and based on a dynamic monitoring of user
activities, such as user queries, user navigation within the web
site, user's interest in particular content of the web site, user's
search/query activities on other web sites such as search engines,
user's activities on social networks, and/or other monitored user
activities).
[0026] In some embodiments, thematic pages optimize torso queries
and/or tail queries by, for example, automatically generating
optimized or enhanced content for the web site to attract queries
for which the web site does not have adequate landing pages. In
some embodiments, the topic or theme is a category-like/torso query
that has high search volume potential, but for which the web site
does not have a relevant existing web page. For example, products
and other content presented on the thematic page can be highly
related and relevant to the main theme. In some embodiments, the
sub-topic or sub-theme is a tail query that has high search volume
potential, but for which the web site does not have a relevant
existing web page.
[0027] In some embodiments, thematic page content includes the
following: a heading or theme; one or more sub-themes (e.g., each
sub-theme can be a targeted query and include, for example, a list
of products or services), widgets showing more products or
services, and related themes or related searches. In addition to
the above, product content can also include a list of related
queries and product/service description, title, and image.
[0028] In some embodiments, generating content for topics based on
user demand includes determining a topic based on a user demand;
automatically generating content for the topic; and selecting the
content that is contextually relevant for display within a corpus
of content. In some embodiments, the content is optimized for the
topic. In some embodiments, the corpus of content includes web
content (e.g., a web site), social content (e.g., a user's social
networking web page), content optimized for mobile devices (e.g.,
content customized for mobile devices), content optimized for
location (e.g., content customized based on location awareness), or
an electronic mail message (e.g., e-mail).
[0029] In some embodiments, the content is displayed in a module of
a corpus of content that includes a plurality of modules, in which
each module includes dynamically generated contextually relevant
content. Example modules can include a Related Searches module, a
Most Popular Products module, a Recent Viewed Products module, a
Your Friends Have Seen module, a Refinements/Related Products
module, and/or various other modules. In some embodiments, a web
site page can be structurally organized to include one or more
modules, in which each module includes dynamically generated
contextually relevant content using various techniques as described
herein. In some embodiments, a module can be provided for content
that is delivered using mechanisms external or independent of the
web site, such as using e-mail sent to one or more users or using
mobile apps executed on user mobile devices (e.g., smart phones,
tablets, laptops, and/or other mobile computing devices).
[0030] In some embodiments, selecting the content that is
contextually relevant for display with a corpus of content further
includes determining the content based on a source of the user
(e.g., a point of origin of the user, such as whether the user is
performing a web search, using a social network, using electronic
mail, using a mobile application (app), and/or any other point of
origin of the user).
[0031] In some embodiments, selecting the content that is
contextually relevant for display with a corpus of content further
includes determining the content based on a temporal element (e.g.,
day-part, week-part, holiday, and seasonality). In some
embodiments, selecting the content that is contextually relevant
for display with a corpus of content further includes personalizing
the content based on user related data. For example, user related
data can include user search history, user purchase history, user
device preference, user presentation preferences, content generated
using pixel log related data, user reviews, social networking
related data (e.g., your friends looked at this), visited
information, and/or any other user related data.
[0032] In some embodiments, selecting the content that is
contextually relevant for display with a corpus of content further
includes determining a placement of the content for integration
with a structure or organization of the corpus of content. For
example, the contextually relevant content can be integrated into
various existing structures of the corpus of content (e.g., using
various different modules, and possibly various different link
structures for a web site) and/or integrating into off-site
content, such as e-mail, mobile app, and/or social content. In some
embodiments, the corpus of content includes a web site, in which
the content includes web page content that is configured or
organized differently than on other web pages of the web site. In
some embodiments, the corpus of content includes a web site, and
the content includes contextually relevant data that does not exist
on other web pages of the web site. In some embodiments, for a
given topic (e.g., theme or sub-theme), a multitude of modules of
contextually relevant content can be generated based on the topic.
In some embodiments, a selection of modules is automatically
configured based on contextual relevancy (e.g., based on a source
of a user, user behavior on the web site and/or off the web site,
and/or where the user is accessing or viewing the module(s), such
as web browsing, e-mail, social network, mobile device, and so
forth).
[0033] In some embodiments, the content is selected for display in
a plurality of modules (e.g., Related Searches module, a Most
Popular Products module, a Recent Viewed Products module, a Your
Friends Have Seen module, a Refinements/Related Products module,
and/or various other modules), and generating content for topics
based on user demand further includes displaying performance
metrics associated with each of the plurality of modules, in which
each of the plurality of modules can be configured or automatically
removed based on the performance metrics. In some embodiments, each
of the plurality of modules is automatically modified based on the
performance metrics. For example, configuration settings can be
selected to automatically decrease or stop using a module or set of
modules based on certain performance metric results, such as based
on threshold settings or performance over a period of time
criteria, and/or any other settings or criteria. In some
embodiments, a charge is determined for using each of the plurality
of modules based on the performance metrics associated with each of
the plurality of modules.
[0034] In some embodiments, generating content for topics based on
user demand further includes analyzing a set of search queries to
determine the topic based on the user demand, in which the set of
search queries include a log of search queries for the web site. In
some embodiments, generating content for topics based on user
demand further includes analyzing an external data source to
determine the topic based on the user demand, in which the external
data source includes social networking resources associated with
the web site and includes social networking resources that include
content that is similar to content included on the web site. For
example, twitter stream or other social data for popular shoes can
be analyzed to determine thematic page content for a shoe
manufacturer. As another example, twitter stream data or other
social data (e.g., Facebook.RTM. pages or Google+.RTM. pages) for a
famous cyclist or for a famous cycling event can be analyzed to
determine thematic page content for a cycling manufacturer. As yet
another example, twitter stream data or other social data (e.g.,
Facebook.RTM. pages or Google+.RTM. pages) that include content
related to a brand or an entity (e.g., which may or may not be
owned, managed, or otherwise associated with controlled by the
brand or the entity) can be analyzed to determine thematic page
content for the brand or the entity.
[0035] In some embodiments, generating content for topics based on
user demand further includes analyzing user behavior to determine
topics based on user demand, in which the analyzed user behavior
includes user search behavior performed on other web sites (e.g.,
user queries on search engines).
[0036] In some embodiments, the corpus of content includes a web
site, in which a landing page of the web site includes the content,
and generating content for topics based on user demand further
includes generating a plurality of configuration of modules for the
topic for the web site, in which each of the plurality of
configuration of modules is optimized for a referring source of
user and a display device type (e.g., and/or other variables, such
as location, day part, and seasonality, operating system (OS) type,
an so forth). For example, a thematic page for a topic, such as
cycling shoes for men or any other topic based on user demand, can
be different based on the user source, such as whether the user is
coming from the Google.RTM. web site, e-mail, or the Facebook.RTM.
web site.
[0037] In some embodiments, the corpus of content includes a web
site, in which a landing page of the web site includes the content,
and generating content for topics based on user demand further
includes adding a link on the web site for the topic, in which the
link is associated with the landing page, and in which the link is
crawlable by a web crawler.
[0038] In some embodiments, generating content for topics based on
user demand further includes automatically anticipate the user
demand (e.g., using various techniques described herein, such as
based on current events, dates, special dates associated with a
user such as birthdays or anniversaries, seasons and/or holidays, a
scheduled or anticipated event such as a major sporting event or
major entertainment event, and/or various other criteria,
parameters, and/or techniques).
[0039] In some embodiments, generating content for topics based on
user demand includes determining a topic based on a user demand;
and automatically generating a landing page for the topic for a web
site. In some embodiments, generating content for topics based on
user demand further includes determining that the web site does not
include existing web page content for the topic; and automatically
generating the landing page for the topic for the web site using
new externally generated web page content. In some embodiments, the
landing page includes web page content that is optimized for the
topic. In some embodiments, the landing page includes web page
content that exists on other web pages of the web site. In some
embodiments, the landing page includes web page content that does
not exist on other web pages of the web site.
[0040] In some embodiments, generating content for topics based on
user demand further includes analyzing a set of search queries to
determine the topic based on the user demand, in which the set of
search queries include a log of search queries for the web site. In
some embodiments, generating content for topics based on user
demand further includes analyzing an external data source to
determine the topic based on the user demand, in which the external
data source includes social networking resources associated with
the web site (e.g., a Facebook.RTM. account or Twitter.RTM. account
associated with the web site).
[0041] In some embodiments, generating content for topics based on
user demand further includes generating a plurality of versions of
the landing page for the topic for the web site, in which each of
the versions of the landing page is optimized for a display device
type or operating system type (e.g., a version for each of the
following a PC browser; a tablet, such as an Apple iPad.RTM.; and a
mobile phone, such as an Apple iPhone.RTM. mobile phone or a Google
Android.RTM. based mobile phone).
[0042] In some embodiments, generating content for topics based on
user demand further includes adding a link on the web site for the
topic, in which the link is associated with the landing page, and
in which a web crawler can crawl the link.
[0043] In some embodiments, generating content for topics based on
user demand includes receiving a user request for a topic at a web
server for a web site, in which the topic is indicated as a linked
topic on a web page of the web site; determining the topic based on
the request; sending a server request for a web page for the topic
to a third party server; receiving the web page for the topic from
the third party server; generating the web page for the topic; in
which a source of the web page for the topic is transparent to a
web crawler. In some embodiments, the server request is
communicated using an application programming interface (API). In
some embodiments, generating content for topics based on user
demand further includes sending the web page for the topic to the
requesting user browser. In some embodiments, generating content
for topics based on user demand further includes caching the web
page for the topic for a period of time or until an event
occurrence.
[0044] FIG. 1 is a functional diagram illustrating a programmed
computer system for generating content for topics based on user
demand in accordance with some embodiments. As shown, FIG. 1
provides a functional diagram of a general purpose computer system
programmed to perform generating content for topics based on user
demand in accordance with some embodiments. As will be apparent,
other computer system architectures and configurations can be used
to perform context sensitive script editing for form design.
Computer system 100, which includes various subsystems as described
below, includes at least one microprocessor subsystem (also
referred to as a processor or a central processing unit (CPU)) 102.
For example, processor 102 can be implemented by a single-chip
processor or by multiple processors. In some embodiments, processor
102 is a general purpose digital processor that controls the
operation of the computer system 100. Using instructions retrieved
from memory 110, the processor 102 controls the reception and
manipulation of input data, and the output and display of data on
output devices (e.g., display 118). In some embodiments, processor
102 includes and/or is used to provide the various
computer/computer implemented functional elements described below
with respect to FIGS. 2, 7, and 8 and/or executes/performs the
processes described below with respect to FIGS. 3 through 6 and
9.
[0045] Processor 102 is coupled bi-directionally with memory 110,
which can include a first primary storage, typically a random
access memory (RAM), and a second primary storage area, typically a
read-only memory (ROM). As is well known in the art, primary
storage can be used as a general storage area and as scratch-pad
memory, and can also be used to store input data and processed
data. Primary storage can also store programming instructions and
data, in the form of data objects and text objects, in addition to
other data and instructions for processes operating on processor
102. Also as well known in the art, primary storage typically
includes basic operating instructions, program code, data and
objects used by the processor 102 to perform its functions (e.g.,
programmed instructions). For example, primary storage devices 110
can include any suitable computer-readable storage media, described
below, depending on whether, for example, data access needs to be
bi-directional or uni-directional. For example, processor 102 can
also directly and very rapidly retrieve and store frequently needed
data in a cache memory (not shown).
[0046] A removable mass storage device 112 provides additional data
storage capacity for the computer system 100, and is coupled either
bi-directionally (read/write) or uni-directionally (read only) to
processor 102. For example, storage 112 can also include
computer-readable media such as magnetic tape, flash memory,
PC-CARDS, portable mass storage devices, holographic storage
devices, and other storage devices. A fixed mass storage 120 can
also, for example, provide additional data storage capacity. The
most common example of mass storage 120 is a hard disk drive. Mass
storage 112, 120 generally store additional programming
instructions, data, and the like that typically are not in active
use by the processor 102. It will be appreciated that the
information retained within mass storage 112, 120 can be
incorporated, if needed, in standard fashion as part of primary
storage 110 (e.g., RAM) as virtual memory.
[0047] In addition to providing processor 102 access to storage
subsystems, bus 114 can be used to provide access other subsystems
and devices as well. As shown, these can include a display monitor
118, a network interface 116, a keyboard 104, and a pointing device
106, as well as an auxiliary input/output device interface, a sound
card, speakers, and other subsystems as needed. For example, the
pointing device 106 can be a mouse, stylus, track ball, or tablet,
and is useful for interacting with a graphical user interface.
[0048] The network interface 116 allows processor 102 to be coupled
to another computer, computer network, or telecommunications
network using a network connection as shown. For example, through
the network interface 116, the processor 102 can receive
information (e.g., data objects or program instructions), from
another network, or output information to another network in the
course of performing method/process steps. Information, often
represented as a sequence of instructions to be executed on a
processor, can be received from and outputted to another network.
An interface card or similar device and appropriate software
implemented by (e.g., executed/performed on) processor 102 can be
used to connect the computer system 100 to an external network and
transfer data according to standard protocols. For example, various
process embodiments disclosed herein can be executed on processor
102, or can be performed across a network such as the Internet,
intranet networks, or local area networks, in conjunction with a
remote processor that shares a portion of the processing.
Additional mass storage devices (not shown) can also be connected
to processor 102 through network interface 116.
[0049] An auxiliary I/O device interface (not shown) can be used in
conjunction with computer system 100. The auxiliary I/O device
interface can include general and customized interfaces that allow
the processor 102 to send and, more typically, receive data from
other devices such as microphones, touch-sensitive displays,
transducer card readers, tape readers, voice or handwriting
recognizers, biometrics readers, cameras, portable mass storage
devices, and other computers.
[0050] In addition, various embodiments disclosed herein further
relate to computer storage products with a computer readable medium
that includes program code for performing various
computer-implemented operations. The computer-readable medium is
any data storage device that can store data which can thereafter be
read by a computer system. Examples of computer-readable media
include, but are not limited to, all the media mentioned above:
magnetic media such as hard disks, floppy disks, and magnetic tape;
optical media such as CD-ROM disks; magneto-optical media such as
optical disks; and specially configured hardware devices such as
application-specific integrated circuits (ASICs), programmable
logic devices (PLDs), and ROM and RAM devices. Examples of program
code include both machine code, as produced, for example, by a
compiler, or files containing higher level code (e.g., script) that
can be executed using an interpreter.
[0051] The computer system shown in FIG. 1 is but an example of a
computer system suitable for use with the various embodiments
disclosed herein. Other computer systems suitable for such use can
include additional or fewer subsystems. In addition, bus 114 is
illustrative of any interconnection scheme serving to link the
subsystems. Other computer architectures having different
configurations of subsystems can also be utilized (e.g., server
devices, appliances with hardware configures for specific
functions, such as a web server or an application server, and/or
various other types of computing devices that can execute various
operating systems and/or virtual machine software techniques).
[0052] FIG. 2 is a functional diagram illustrating network based
search in accordance with some embodiments. For example, the
Internet and, in particular, the World Wide Web (WWW), includes
searchable content located on various computers, servers, and
network appliances (e.g., web servers/appliances). Web browsers,
such as web browser 220, provide client software executed on a
computer, such as client 210, for accessing searchable content
(e.g., web pages) on the WWW, such as searchable content provided
by a server 240 (e.g., Nike's web site) and/or competitor
searchable content provided by a server 250 (e.g., Adidas' web
site). As shown in FIG. 2, the client computer 210 submits a query
to the search engine 230 and receives search results back from the
search engine 230 (e.g., Google's search engine, Yahoo' search
engine, Microsoft's Bing search engine, or another search engine).
The search engine 230 provides search results based on the query
received from the client 210. The search engine 230 typically
crawls various searchable content on the network, (e.g., crawlable
content on WWW sites) including searchable content 240 and 250 to
identify relevant searchable content (e.g., to update an index of
available searchable content). The search engine 230 typically
provides natural or organic search results based on the query and,
in some cases, can also provide paid search results (e.g., based on
paid keywords in the query submitted by the client 210 or based on
other techniques). As will be appreciated by those of ordinary
skill in the art, various network architectures and
software/computing solutions are available for providing network
based search. In some embodiments, generating content for topics
based on user demand can be used, for example, by a web site
operator providing searchable content 240 by providing various
modules for topics based on user demand in which each module
includes dynamically generated contextually relevant content as
described herein using various techniques. For example, modules
based on a topic can be generated that include links added to new
landing pages for the topic on a one or more HTML pages of the web
site providing the crawlable and searchable content 240 (e.g., in a
module for providing related searches, a module for related topics,
and/or a module for related themes, which can be presented in a
sub-section of the web page, in which the web page can be divided
to provide for including one or more such modules).
[0053] FIG. 3 is a flow diagram for generating content for topics
based on user demand in accordance with some embodiments. At 302, a
topic (e.g., theme or sub-theme) based on user demand is
determined. In some embodiments, user demand is determined by
analyzing user activities on the web site and/or user activities
off of the web site. For example, the topic can be determined by
analyzing search query logs for the web site (e.g., millions of
user queries for the web site) and/or analyzing search query logs
for search engines (e.g., millions of user queries on one or more
search engines. The search query logs are analyzed to identify
common sets of terms and phrases that describe a set of products
(e.g., similar techniques can be applied to other data sources,
such as social network related sources that may or may not be
associated with the web site, as discussed herein). Once these
phrases are identified, these phrases can then be passed through an
inverse search engine that includes, for example, a series of
scoring and filters to identify terms or phrases of interest (e.g.,
a high frequency of certain terms or phrases, which score
relatively highly using various scoring and filtering techniques,
can be indicative of user demand); and such terms or phrases that
are high scoring and non-duplicative of the web site's existing
content can then be selected and launched as topics using various
techniques described herein. For example, referring to the
furniture web site example, the query search logs can be analyzed
to determine that there is a high frequency of bi-grams that
include the terms "leather" and "chair" (e.g., "leather arm chair",
"reclining leather chair", and so forth). By extracting
topics/sub-topics (e.g., themes/subthemes) based on query/product
matching analysis can identify matching words in queries to
generate new potential themes/sub-themes, such as leather
chair/leather reclining chair). The themes can be sorted based on
common words, and then clustered (e.g., using a min hash
clustering, n-squared clustering based on bi-grams, or using
various other clustering techniques) to generate potential queries
of interest. Also, sub-themes using word match or based on common
products matching such queries and, in some cases, can further
determine if a user issues a refinement search based on session
data (e.g., session ID, referring URL, referring query, and/or time
stamp for every log, which allows for this type of
determination/extraction that user first searched for leather chair
than searched for reclining leather chair). Next, products that
match leather chair (e.g., p1, p2, p3, . . . , pn, etc.) can be
determined, and then page content, name of product, tags, users
landed on page and stayed for a period of time can be determined.
In some cases, these themes/sub-themes can further be filtered
based on whether the web site is determined to have adequate
existing content/structure (e.g., if not, then a new landing page
for the theme/sub-theme can be generated to extend the web site to
include the new thematic landing page to thereby enhance the web
site's structure and/or content for the theme).
[0054] In some embodiments, web pages based on product and
attribute information are be generated using various techniques as
described herein. For example, for each product on a web site,
product names can be analyzed to extract various attributes (e.g.,
colors, size, units, and/or other attributes) and product names. In
some embodiments, extracting such attributes is determined by
issuing various queries against a product index for the web site;
two products are deemed similar if they match a threshold number of
queries; for each pair of similar products, common strings are
extracted; among the extracted strings, known attributes such as
colors, units, size, and/or other attributes are extracted; in the
remaining string, the longest matching string at the highest
position is determined to be the product name; and everything else
is indicated as attributes. For each product-attribute pair, the
number of matching products is computed. If the number of matching
products exceeds a specified threshold value, a page is created for
this product-attribute pair. For example, for a running gear web
site, for the products: "All-weather Men's Running Shoes" and
"Comfortable Nike Men's Running Shoes", various attributes can be
extracted, such as "Canvas", "Comfortable", "All-weather", "Nike"
can be extracted as attributes and "Men's Running Shoes" can be
determined to be the product. In this example, web pages based on
product and attribute information such as the following can be
generated: "Comfortable Men's Running Shoes" and "Canvas Men's
Running shoes."
[0055] In some embodiments, ontology based pages are generated
using various techniques as described herein. In some embodiments,
the navigational content of a web site (e.g., menus, breadcrumbs,
refinements etc) are scraped. For each of these scraped elements,
the number of matching products is computed. If the number of
matching products is large enough (e.g., exceeds a threshold
value), a page is generated for this element. For example, if a
given web site has a category page for "Dishwashers", and the
refinements on the page are Color and Brand, then generated new
pages can include, as examples, the following: "Gray Dishwashers"
and "Kenmore Dishwashers."
[0056] In some embodiments, structured content based pages are
generated using various techniques as described herein. As an
example, a web site's content is structured into units. Each unit
can either be a single piece of information, a class of
information, or a collection of information. Units can then be
analyzed to compute as to how relevant they are to other units.
This process can be manual or can be automated. If the above
frequencies are high, the units can be paired together. Blocks of
such units can now form a page, after incorporating some other meta
information. For example, a web site can have units of information,
such as "Flights from LA to NY", "Hotels near Chicago airport",
"Bus from LA to SFO", "Car Rentals near SFO airport", etc. After
analyzing the web site, "Flights from X to Y" can be determined to
be relevant to "Car rental near Y" and "Hotels near Y airport", but
determined to not be relevant to "Hotels near X airport" or "Bus
from X to Y". As a result, a page can be generated about "Flights
from X to Y" with the determined relevant information.
[0057] At 304, content for the topic is automatically generated. At
306, the content that is contextually relevant for display within a
corpus of content is selected. In some embodiments, a potential
query is discarded, because the web site is determined to not have
sufficient content to generate a new landing page for the query
(e.g., in some cases, if a query meets a certain threshold, but the
web site lacks sufficient content to generate a landing page for
the query, then a notification can be sent to the web site owner
and/or a log can be generated to indicate this determination, thus
allowing the web site owner to potentially develop content for
adding to the web site to manually add a page or to allow the
techniques described herein to automatically generate a new landing
page for a theme corresponding to such newly added web site content
based on the query).
[0058] FIG. 4 is another flow diagram for generating content for
topics based on user demand in accordance with some embodiments. At
402, a topic (e.g., theme or sub-theme) based on user demand is
determined. At 404, content for the topic is automatically
generated. At 406, a plurality of modules for the topic is
automatically generated. At 408, the content that is contextually
relevant for display within a corpus of content is selected.
[0059] FIG. 5 is another flow diagram for generating content for
topics based on user demand in accordance with some embodiments. At
502, that the web site does not include existing web page content
for the topic is determined. At 504, a landing page for the topic
is automatically generated for the web site (e.g., which can be
provided as a module for the topic, as a new web page for the
topic, and/or as new content for the topic for an existing web
page). At 506, whether to link the new landing page for the topic
is determined. For example, a network administrator can be
contacted to confirm whether or not to add the link to the new
landing page. As another example, a network administrator can be
contacted, and if no response is received (e.g., within a
predetermined period of time), the link to the new landing page can
automatically be added to the web site, or alternatively, if no
response is received, the link to the new landing page will not be
added. As yet another example, an automatic workflow process for
approval of adding such new landing pages that include externally
generated web page content can be executed. At 508, assuming it is
determined that the new landing page should be added to the web
site, a link is added to the landing page from the web site.
[0060] FIG. 6 is another flow diagram for generating content for
topics based on user demand in accordance with some embodiments. As
discussed above, user demand can be determine using various
techniques described herein. At 602, a set of search query logs
(e.g., search query logs associated with a web site) are analyzed
to determine a topic based on the user demand. At 604, an external
data source is analyzed to determine the topic based on the user
demand. For example, the external data source can include social
networking resources (e.g., social networking resources associated
with the web site and includes social networking resources that
include content that is similar to content included on the web
site) and/or other external data sources. As another example, the
external data source can include search engine search query logs.
In some embodiments, user related data is analyzed to determine
user demand and/or to determine contextually relevant content for a
given user. For example, user related data can include user search
history, user purchase history, user device preference, user
presentation preferences, content generated using pixel log related
data, user reviews, social networking related data (e.g., your
friends looked at this), visited information, and/or any other user
related data.
[0061] FIG. 7 is a functional diagram illustrating a web page
including links to topics based on user demand in accordance with
some embodiments. As shown, a web page 700 includes a "Related
Searches" sub-section or sub-window 702, which includes links. In
some embodiments, the Related Searches sub-section 702 includes
links, in which at least some of the links include links to landing
pages for topics or themes. In some embodiments, links to landing
pages are included in other sections 704, 706, and 708 (e.g.,
Related Topics or Related Sub-Topics or Related Searches) or
integrated into various pages of corpus of content of a web
site.
[0062] In some embodiments, various modules are automatically
generated for a topic or sub-topic (e.g., a theme or sub-theme).
For example, the modules can be selected to provide contextually
relevant content (e.g., based on the web site, a source of a user,
a device being used by the user, and so forth) and can provide an
optimal landing page for user queries that are not otherwise
optimally captured by the web site's existing content or structure.
In some embodiments, various modules are provided that provide the
content for the topic (e.g., a Related Searches module, a Most
Popular Products module, a Recent Viewed Products module, a Your
Friends Have Seen module, a Customer Favorites module, a
Refinements/Related Products module, and/or various other
modules).
[0063] In some embodiments, the customer favorites module presents
the highest ranking products that match the main theme (e.g., based
on scoring techniques as described herein). For example, the
customer favorite's module facilitates the display of product
assortments that are most relevant to the theme and expected to
generate a significant portion of user clicks. Also, search engines
can crawl this content, which generally facilitates improved
indexing and eventually ranking of the product pages linked, based
on the optimized keywords present in the content. In some
embodiments, these products are computed by analyzing user click
behavior and combining that with relevancy rating to create a
score. If the site has more information about products (e.g.,
ratings, reviews, and/or other information about products), this
data will also be used to compute the product's relevancy
score.
[0064] In some embodiments, the top refinements module presents a
set of queries (e.g., or sub-themes) that are highly relevant
refinements to the base theme or main theme. For example, the
sub-themes improve user navigation, providing users with commonly
used additional options for the broad theme that they are
exploring. Also, sub-themes and their associated content can
generally improve keyword density and increase search engines'
access and crawling of more keywords for the base theme than would
be present on an existing product or category page. In some
embodiments, sub-themes are computed by determining relatedness of
the sub-theme to the base theme and analyzing user click data and
behavior. For example, sub-themes can be generated and presented
with minimal overlap between each other, to increase diversity on
the page and maximize the number of unique keywords on the
page.
[0065] In some embodiments, related themes are provided as links in
a sub-window (e.g., such as sub-window 702). In some embodiments,
these are links to other thematic pages that are relevant to the
present page (e.g., web page 700). For example, users can navigate
to related content and explore additional products and themes that
are related to the present thematic page. Also, these links are
crawlable and, thus, can help search engines discover other
thematic pages. In some embodiments, these links are computed based
on product relevancy and product overlap (e.g., and can also be
presented in a "Related Searches" widget).
[0066] In some embodiments, related searches are provided as links
in a sub-window (e.g., such as sub-window 702). In some
embodiments, these are links to other search results pages that are
relevant to this page. For example, the related searches can
suggest searches that are common on the site related to the given
theme. Also, these links can help search engines discover other
search pages, and these links can bring in valuable and relevant
content onto the given page. In some embodiments, these links are
computed based on product relevancy and product overlap; and these
searches are typically high frequency (e.g., and can also be
presented in a "Related Searches" widget).
[0067] In some embodiments, "More Results" are provided as links in
a sub-window (e.g., such as sub-window 702). In some embodiments,
these are links to (1) other Thematic Pages, if they exist, or (2)
search results pages if there are no relevant Thematic Pages. For
example, these links allow users to further explore the assortment
of products presented in the "Top Refinements" sub-themes. Also,
these links can facilitate crawling by search engines to search
other pages and thematic pages for the web site.
[0068] FIG. 8 is a network architecture for generating content for
topics based on user demand in accordance with some embodiments. As
shown, a client device 810 that executes a web browser 820 is in
network communication with a web site 830 (e.g., a server or
appliance or other web or cloud based network service that services
requests for the web site). In particular, the client browser 820
requests a theme landing page (e.g., a web page that is optimized
for a particular theme). The web site 830 determines that the
request includes a request for a landing page for a theme. In some
embodiments, the web site 830 determines whether a copy of the
landing page for the theme has been locally cached. Assuming that
the web site does not have a local copy of the landing page for the
theme, the web site 830 submits a request for the landing page for
the theme to a theme content service 840 (e.g., a server or
appliance or other web or cloud based network service that services
requests for theme landing pages for the web site). The theme
content service 840 returns the landing page for the theme to the
web site 830, which then sends the landing page for the theme to
the browser 820 (e.g., which can render the landing page for the
theme for display by the client device 810).
[0069] In some embodiments, a web site includes links to theme
based landing pages for the web site (e.g., links to thematic
pages). For example, when a user clicks a link to a thematic page,
the exact URL pattern used can take several forms (e.g.,
http://www.<merchant>.com/<page_name>-th.html). The web
site server can extract the page_name field from the URL (e.g., as
indicated in the above example) and can construct a fetch_thematic
API call to a third party theme content service (e.g., the remote
API can require an HTTP GET request that specifies, and possibly
authenticates the authorized web site requester using a private
key, and also possibly utilizes a variable number of HTTP
parameters escaped using URL percent-encoding conventions, the
requesting web site and the requested thematic page) that services
thematic page requests for the web site (e.g., in other examples,
the thematic page requests can be serviced by the web site server
or another service managed by the web site operator). The third
party theme content service can then return the requested thematic
page (e.g., return the HTML for the requested thematic page,
possibly inside returning the HTML that should be used to construct
the thematic page by placing the returned HTML inside a thematic
page template). The web site server can then construct the thematic
page using the returned HTML page, and possibly some additional
boilerplate, and can then return the requested constructed thematic
page to the requesting user's client browser. In some embodiments,
the web site server caches the thematic pages (e.g., for a one day
period of time, or another period of time or based on an event
occurrence).
[0070] FIG. 9 is another flow diagram for generating content for
topics based on user demand in accordance with some embodiments. At
902, a user request for a topic (e.g., theme or sub-theme) is
received at a web server for a web site. At 904, the topic is
determined based on the request. At 906, a third party server
request for a web page for the topic is sent. At 908, the web page
for the topic is received at the web server for the web site. At
910, the web page for the topic is generated at a client device
browser. In some embodiments, a source of the web page for the
topic is transparent to a web crawler.
[0071] Although the foregoing embodiments have been described in
some detail for purposes of clarity of understanding, the invention
is not limited to the details provided. There are many alternative
ways of implementing the invention. The disclosed embodiments are
illustrative and not restrictive.
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References