Source: http://www.google.com/patents/US7539674?ie=ISO-8859-1
Timestamp: 2014-07-13 04:22:47
Document Index: 46020279

Matched Legal Cases: ['Application No. 60', 'art 200', 'art 200', 'art 200', 'art 200', 'art 200', 'art 200', 'art 200']

Patent US7539674 - Systems and methods for adaptive scheduling of references to documents - Google PatentsSearch Images Maps Play YouTube News Gmail Drive More »Sign in<nobr>Advanced Patent Search</nobr>PatentsMethods, computer systems, and computer program products for adaptive scheduling of references to documents include a document data structure and a document selection module. The document data structure comprises a plurality of documents. Each respective document in the plurality of documents has (i)...http://www.google.com/patents/US7539674?utm_source=gb-gplus-sharePatent US7539674 - Systems and methods for adaptive scheduling of references to documentsAdvanced Patent SearchPublication numberUS7539674 B2Publication typeGrantApplication numberUS 10/897,064Publication dateMay 26, 2009Filing dateJul 22, 2004Priority dateApr 8, 2004Fee statusPaidAlso published asUS8214358, US8706722, US20050229094, US20090013006, US20120239490Publication number10897064, 897064, US 7539674 B2, US 7539674B2, US-B2-7539674, US7539674 B2, US7539674B2InventorsJeffrey E. F. Friedl, Kathleen L. HartnackOriginal AssigneeYahoo! Inc.Export CitationBiBTeX, EndNote, RefManPatent Citations (9), Referenced by (1), Classifications (10), Legal Events (2) External Links: USPTO, USPTO Assignment, EspacenetSystems and methods for adaptive scheduling of references to documentsUS 7539674 B2Abstract Methods, computer systems, and computer program products for adaptive scheduling of references to documents include a document data structure and a document selection module. The document data structure comprises a plurality of documents. Each respective document in the plurality of documents has (i) a corresponding designation of a number of times the respective document was requested in a given time period and (ii) a corresponding selection weight. The document selection module includes, for each respective document in the plurality of documents, instructions for monitoring a number of times the respective document is requested in the given time period. The document selection module also has instructions for updating the number of times the respective document was requested in the given time period as well as instructions for adjusting the selection weight corresponding to the respective document based upon the number of times the respective document was requested relative to a total number of document requests during a given time period.
1. A computer program product for use in conjunction with a computer, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising:
(A) a document data structure comprising a plurality of documents, each respective document in the plurality of documents including a corresponding:
designation of a number of times the respective document was requested in a predetermined time period; and
selection weight, wherein the selection weight corresponds to a relative popularity of the respective document; and
(B) a document selection module that includes, for each respective document in said plurality of documents:
instructions for monitoring a number of times the respective document is requested in said predetermined time period;
instructions for updating the number of times the respective document was requested in the predetermined time period;
instructions for adjusting the selection weight corresponding to the respective document based upon a number of times the respective document was requested in the predetermined time period relative to a total number of document requests during the predetermined time period;
instructions for adjusting the selection weight upon removal of one of the plurality of documents, wherein a selection weight for each respective document in the plurality of documents is increased based on the removal of a document;
instructions for adjusting the selection weight upon an addition of a document to the plurality of documents, wherein a selection weight for each respective document in the plurality of documents is decreased based on the addition of a document;
instructions for automatically decreasing the selection weight for the respective document as the respective document is displayed over time; and
instructions for providing an interface for receiving a manual adjustment of the selection weight.
2. The computer program product of claim 1 wherein the document data structure further comprises a header for each respective document in all or a portion of the plurality of documents.
3. The computer program product of claim 2 wherein the document selection module further comprises:
instructions for receiving a request for a host web page;
instructions for selecting a subset of said plurality of documents as a function of the respective selection weight of each document in said plurality of documents; and
instructions for posting to said host web page, for each respective document in the subset of said plurality of documents, the header corresponding to the respective header.
4. The computer program product of claim 1, wherein said document selection module further comprises instructions for adding a new document to said document data structure, wherein said instructions for adding include instructions for assigning a grace period selection weight to said new document.
5. The computer program product of claim 4 wherein said grace period selection weight is the percentile 1/N, where N is a number of documents in said document data structure, including said new document, and wherein said document selection module further comprises: instructions for reducing, for each respective document in the document data structure other than the new document, the selection weight of the respective document by [(N−1)/N] percent.
6. The computer program product of claim 1, wherein for the addition of a document to the plurality of documents, a grace period selection weight for the added document is proportional to an inverse of a total number of document requests for the plurality of documents.
7. The computer program product of claim 1 wherein said predetermined time period is between one minute and five hours.
8. The computer program product of claim 3 wherein a probability that a respective document in said document data structure will be selected for said subset of said plurality of documents by said instructions for selecting is equal to the selection weight of the document.
9. The computer program product of claim 1 wherein the document in the plurality of documents is a news article or a description of an investment idea.
10. A computer program product for use in conjunction with a computer, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising:
first designation of a number of times the respective document was requested in a predetermined time period by a first class of users;
second designation of a number of times the respective document was requested in said predetermined time period by a second class of users;
first selection weight, wherein the first selection weight determines which of the respective documents of the plurality of documents are displayed for the first class of users;
second selection weight, wherein the second selection weight determines which of the respective documents of the plurality of documents are displayed for the second class of users; and
a feature indicia field corresponding with indicia of the respective document that is provided based on the class of users; and
instructions for adjusting the first selection weight corresponding to the respective document based upon the number of times the respective document was requested in said predetermined time period by said first class of users relative to a total number of document requests by said first class of users during said predetermined time period;
instructions for adjusting the second selection weight corresponding to the respective document based upon the number of times the respective document was requested in said predetermined time period by said second class of users relative to a total number of document requests by said second class of users during said predetermined time period; and
instructions for providing the indicia of the respective document based on the class of users, wherein a first indicia of the respective document is provided for the first class of users and a second indicia of the respective document is provided for the second class of users.
11. The computer program product of claim 10, wherein the computer program mechanism further comprises a profile management module, the profile management module comprising instructions to determine a class of each respective user requesting a document by accessing a user profile associated with the respective user.
12. The computer program product of claim 10 wherein each user in said first class of users is associated with a first geographical region and each user in said second class of users is associated with a second geographical region.
13. The computer program product of claim 10 wherein each user in said first class of users is a first gender and each user in said second class of users is a second gender.
14. The computer program product of claim 10 wherein each user in said first class of users is in a first age range and each user in said second class of users is in a second age range.
15. The computer program product of claim 10 wherein each user in said first class of users speaks a first primary language and each user in said second class of users speaks a second primary language.
16. The computer program product of claim 10 wherein each user in said first class of users is in a first income bracket and each user in said second class of users is in a second income bracket.
17. The computer program product of claim 10 wherein the document in the plurality of documents is a news article or a description of an investment idea.
18. A computer for identifying documents of interest to users, the computer comprising:
a memory, coupled to the central processing unit, the memory storing a document data structure and a document selection module, wherein
the document data structure comprises a plurality of documents, each respective document in the plurality of documents including a corresponding:
selection weight, wherein the selection weight determines which of the respective documents of the plurality of documents are displayed; and
the document selection module includes, for each respective document in the plurality of documents:
instructions for updating said number of times the respective document was requested in said predetermined time period;
instructions for adjusting the selection weight corresponding to the respective document based upon the number of times the respective document was requested in said predetermined time period relative to a total number of document requests during said time period;
instructions for adjusting the selection weight upon removal of one of the plurality of documents or an addition of a document to the plurality of documents, wherein a selection weight for each respective document in the plurality of documents is adjusted based on the addition or removal of a document; and
instructions for automatically decreasing the selection weight for the respective document as the respective document is displayed over time.
19. A computer for identifying documents of interest to users, the computer comprising:
first selection weight, wherein the first selection weight corresponds to a relative popularity of the respective document with the first class of users;
second selection weight, wherein the second selection weight corresponds to a relative popularity of the respective document with the second class of users; and
the document selection module includes, for each respective document in said plurality of documents:
20. The computer of claim 19, wherein the computer program mechanism further comprises a profile management module, the profile management module comprising instructions to determine a class of each respective user requesting a document by accessing a user profile associated with the respective user.
21. A computer implemented method for providing documents of interest to a user on a host web page, the method comprising:
(i) receiving, by a processor, a request to view an instance of said host web page;
(ii) selecting a subset of documents from a plurality of documents based on a selection weight associated with each respective document in the plurality of documents;
(iii) identifying a class of the user;
(iv) posting a description of each document in said subset of documents to said host web page, wherein each description comprises an indicia of each respective document;
(v) monitoring which documents in said subset of documents posted to said host web page are selected by a user;
(vi) repeating (i) through (v) for each request to view an instance of said host web page that is received during a predetermined time period;
(vii) adjusting, for each respective document in the plurality of documents, the selection weight associated with the respective document based upon a number of times the respective document was selected by a user relative to a total number of times a document in the plurality of documents was selected by a user in the predetermined time period; and
(viii) adjusting, for each respective document in the plurality of documents, the selection weight associated with the respective document upon an addition of a document to the plurality of documents, wherein the selection weight for each respective document in the plurality of documents is reduced and the additional document is assigned a grace period selection weight for an initial grace period that is inversely proportional to the number of the plurality of documents.
22. The method of claim 21 wherein each said description of a document provides a title of the document, wherein a user selects the document by clicking on the title of the document.
23. The method of claim 21 wherein said grace period selection weight is the percentile 1/N, where N is a number of documents in said plurality of documents, including said new document, the method further comprising: reducing, for each respective document in the plurality of documents other than the new document, the selection weight of the respective document by [(N−1)/N] percent.
24. The method of claim 21 wherein a probability that a respective document in said plurality of documents will be selected for said subset of documents during said selection (ii) is equal to the selection weight of the document.
25. The method of claim 21, the method further comprising: removing a document from said plurality of documents and, for each remaining respective document in the plurality of documents, adjusting the selection weight corresponding to the respective document based upon the number of times the respective document was requested in said predetermined time period relative to a total number of document requests during said predetermined time period.
26. The method of claim 21 wherein said predetermined time period is between one minute and five hours.
27. A computer program product for use in conjunction with a computer, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising:
(A) a teaser data structure comprising a plurality of teasers for a document, each respective teaser comprising an indicia related to the document that is provided as an indication of the document, wherein each respective teaser in the plurality of teasers includes a corresponding:
designation of a number of times the document was requested in a predetermined time period while the respective teaser was being displayed on a host web site; and
selection weight, wherein the selection weight corresponds to a relative popularity of the respective teaser; and
(B) a teaser selection module that includes, for each respective teaser in the plurality of teasers:
instructions for monitoring a number of times the document is requested in the predetermined time period while the respective teaser was being displayed on the host web site;
instructions for updating the teaser data structure to include the number of times the document was requested in the predetermined time period while the respective teaser was being displayed on the host web site;
instructions for adjusting the selection weight corresponding to the teaser based upon a number of times the document was requested by users in the predetermined time period while the teaser was being displayed on the host web site relative to a total number of times the document was requested by users in the predetermined time period;
instructions for adjusting the selection weight corresponding to the teaser upon removal of one of the plurality of documents, wherein a selection weight corresponding to the teaser for each respective document in the plurality of documents is increased based on the removal of a document;
instructions for adjusting the selection weight corresponding to the teaser upon an addition of a document to the plurality of documents, wherein a selection weight corresponding to the teaser for each respective document in the plurality of documents is decreased based on the addition of a document; and
instructions for selecting a teaser from the plurality of teasers for the document based on the selection weight of the teasers in the plurality of teasers and providing the selected teaser as an indication of the document.
28. A computer implemented method for providing documents of interest to a user on a host web page, the method comprising:
(iii) posting a description of each document in said subset of documents to said host web page;
(iv) monitoring which documents in said subset of documents posted to said host web page are selected by a user;
(v) repeating (i) through (iv) for each request to view an instance of said host web page that is received during a predetermined time period;
(vi) adjusting, for each respective document in the plurality of documents, the selection weight associated with the respective document based upon a percentage of the total number of document requests by users attributed to the respective document during said predetermined time period relative to the percentage of time the respective document is selected for inclusion in a subset of documents by said selecting (ii);
(vii) adjusting, for each respective document in the plurality of documents, the selection weight associated with the respective document upon an addition of a document to the plurality of documents, wherein the selection weight for each respective document in the plurality of documents is reduced and the additional document is assigned a grace period selection weight for an initial grace period that is inversely proportional to the number of the plurality of documents; and
(viii) automatically decreasing the selection weight for the respective document as the respective document is displayed over time.
29. The method of claim 28 wherein the selection weight associated with a document in the respective documents is increased in said adjusting (vi) when the percentage of the total number of document requests by users attributed to the document during the predetermined time period is greater than the percentage of time the respective document is selected for inclusion in said subset of documents.
30. The method of claim 28 wherein the selection weight associated with a document in the respective documents is decreased in said adjusting (vi) when the percentage of the total number of document requests by users attributed to the document during the predetermined time period is less than the percentage of time the respective document is selected for inclusion in said subset of documents. Description
CROSS-REFERENCE TO RELATED APPLICATIONS This application claims benefit, under 35 U.S.C. � 119(e), of U.S. Provisional Patent Application No. 60/561,142, filed on Apr. 8, 2004, which is hereby incorporated by reference in its entirety.
FIELD OF THE INVENTION This invention relates to systems and methods for adaptive scheduling of references to documents. The references are included as components of a web page that is made available to a user population.
BACKGROUND OF THE INVENTION The hosting of web portals such as Yahoo.com is competitive. Central to such businesses is the attraction of a large number of users to the portal and keeping such users interested in the portal content. Portal search engine quality is one method for attracting users. However, more is needed to keep users at the portal site, as opposed to linking away from the portal to sites identified by search engine results. Although the way in which advertising revenues are computed can vary, such revenues are generally dependent upon not only the number of viewers that are attracted to a portal, but also the length of time such users stay at the portal. Therefore, portals have worked to extend the amount of interesting content that is found directly at the portal in order to retain users at the portal.
SUMMARY OF THE INVENTION The present invention provides systems and methods for gauging user interest in topics such as news articles. In one embodiment, a panel of candidate documents is gathered by an editor. To reduce screen clutter, only references to a subset of the panel of documents is displayed on a web site at any given time. In fact, each time a user opens the web site, a different subset of the panel of documents is selected and references to the selected documents are displayed. Each candidate document is assigned a weight. Candidate documents are included in a displayed subset of documents as a function of their weight. More heavily weighted documents will be selected for display more frequently than less heavily weighted documents. The number of times users select each document is tracked over a look back period. Documents that have been frequently selected by users are reassigned heavy weights and documents that have been infrequently chosen are assigned lighter weights. In this way, screen clutter is avoided, while, at the same time, user feedback is used to reinforce the weights of documents that are of interest to users.
BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 illustrates a computer system capable of scheduling the appearance of references to topics of interest on a web site in accordance with one embodiment of the present invention.
DETAILED DESCRIPTION The present invention provides systems and methods for identifying documents of interest to users. Typically, such documents are news and editorial articles, advertisements, teaser content for features of a web site, and the like.
System Overview A system 10 that supports functionality of the present invention is described in conjunction with FIG. 1. System 10 preferably includes:
a central processing unit (CPU) 22 (e.g., a full CPU such as an Intel pentium processor, an application-specific integrated circuit, a field-programmable gate array, or the like); a main non-volatile storage unit 14, for example a hard disk drive, for storing software and data, the storage unit 14 controlled by storage controller 12; a system memory 36, preferably high speed random-access memory (RAM), for storing system control programs, data, and application programs, including programs and data loaded from non-volatile storage unit 14; system memory 36 may also include read-only memory (ROM); a user interface 32, including one or more input devices (e.g., keyboard 28, mouse) and a display 26 or other output device; communications circuitry 20 for connecting to any wired or wireless communication network such as the Internet 34; a power source 24; an internal bus 30 for interconnecting the aforementioned elements of system 10. Operation of system 10 is controlled primarily by operating system 40, which is executed by central processing unit 22. Operating system 40 can be stored in system memory 36. In a typical implementation, system memory 36 includes:
As further illustrated in FIG. 1, system 10 optionally includes a user profile database 62. Like document database 50, user profile database 62 comprises any form of data storage system, including but not limited to, a flat file, a relational database (SQL), and an on-line analytical processing (OLAP) database (MDX and/or variants thereof). In some specific embodiments, user profile database 62 is a hierarchical OLAP cube. In some specific embodiments, user profile database 62 comprises a star schema that is not stored as a cube but has dimension tables that define hierarchy. Still further, in some embodiments, user profile database 62 has hierarchy that is not explicitly broken out in the underlying database or database schema (e.g., dimension tables that are not hierarchically arranged).
The embodiment illustrated in FIG. 1 is that of a computer-based implementation of the present invention. In some embodiments in accordance with FIG. 1, document selection module 44 and/or profile management module 60 is implemented as a web-based application that can be run in a browser such as Windows Explorer or Netscape Navigator. In some embodiments, document selection module 44 and/or profile management module 62 are implemented as independent programs that can be run directly through operating system 40.
Tracking Document Requests Line 202 of chart 200 (FIG. 2) discloses the total number of document requested from a host web page 70 at discrete time periods (predetermined time periods) during a given Friday. For example, chart 200 shows how there are more document requests at 9:00 A.M. then at 2:00 A.M. For comparative purposes, line 204 of chart 200 shows the median number of document requests that were made during comparable periods on other Fridays. Further, lines 206 of chart 200 shows the median number of document requests that were made during comparable periods on all days. For example, line 202 of chart 200 indicates that some 116,193 document requests were made between 9:00 A.M. and 10:00 A.M. on a particular Friday represented by the graph. Line 204 of chart 200 indicates that, historically, some 119,230 document requests are made between 9:00 A.M. and 10:00 A.M. on Fridays. Next, line 206 of chart 200 indicates that, historically, 118,999 documents are requested between 9:00 A.M. and 10:00 A.M. Advantageously, in accordance with the methods of the present invention, the information disclosed in FIG. 2 is used to determine which subset of documents links in a plurality of documents links should be displayed on the host web page 70.
FIG. 3 illustrates the concept of tracking links to documents. In FIG. 3, the titles of three news articles are depicted. Here, the titles of the three news articles serves as links to the news articles. Each title is displayed on a host web page 70 (FIG. 1). When a user selects a title they are redirected to the corresponding news article. As such, each news article is considered a document 52. The database 50 illustrated in FIG. 3 also shows the number of times each of the news articles is requested from a host web page 70. For example, the database 50 shows that the news article �Can the Dow accurately predict the market?� was selected by users between 8:00 A.M. and 9:00 A.M. a total of 2,228 times. The value 2,228 is stored in the field 54 that corresponds to this news article in database 50.
In the embodiment of database 50 illustrated in FIG. 3, the selection weight 56 of each news article is shown. For example, the news article �Can the Dow accurately . . . � 52-1 has a selection weight 56-1 of eleven percent. This means that the title or some other indicia of news article 52-1 will be selected for display on host web page 70 eleven percent of the time. News article �No Agreement to outsourcing?� 52-2 has a selection weight 56-2 of thirteen percent. This means that the title or some other indicia of news article 52-2 will be selected for display on host web page 70 thirteen percent of the time.
Automated Up-Weighting and Down-Weighting Methodologies Referring to FIG. 4, a method for automatically adjusting selection weights 56 assigned to documents in document database 50 is disclosed.
The title of each document 52 in the selected subset of documents is displayed on the host web page 70. For example, consider the case in which documents 52-1 and 52-3 were selected for inclusion in the subset of documents in an instance of step 404. Then, the title of document 52-1 (�Can the Dow predict . . . ?�) and the title of document 52-3 (�Is it a bull market?�) is displayed on host web page 70. In a preferred embodiment, when the user refreshes host web page 70, a whole other instance of step 404 is initiated in which a new subset of documents 52 is selected from document database 50 for display on host web page 70 based on selection weights 56. Thus, in the example above, refreshing host web page 70 can cause documents 52-1 and 52-3 to be replaced by any pair of documents 52 from document database 50 (e.g., documents 52-1 and 52-5).
TABLE 2 Exemplary document database 50 at step 406 Selection Weight (56) Number of Document (52) [Percentile] Indicia/Link hits (54) 52-1 50 Can the Dow 350 predict . . . ? 52-2 10 No agreements 100 52-3 10 Is it a bull market? 80 52-4 10 Title of document 4 200 52-5 10 Title of document 5 0 Table 2 shows that, although a link to document 52-4 has the same probability of appearing on host web page 70 as documents 52-2, 52-3, and 52-5 during the look back period, the document has received considerably more page hits than the other documents. In fact, the number of page hits that document 52-4 has received is almost comparable to the number of page hits that document 52-1 has received, even though a reference (link) to document 52-1 appears on instances of host web page 70 fives times more frequently than does a link for document 52-4.
Step 408. In step 408, a determination is made as to whether a predetermined time interval, referred to herein as a look back period, has elapsed. In some embodiments, the look back period is a second, a minute, five minutes, one half hour, an hour. In other embodiments, the look back period is a predetermined value between one second and five hours. If the look back period has not elapsed (408�No) process control returns to step 404 where host web page hits 70 are processed in the manner described in steps 404 and 406 above.
In addition to the expiration of a predetermined time period, step 408 can be triggered (caused to enter the state 408�Yes) when an editor decides to add or remove a document from document database 50. In preferred embodiments, such events initiate a recomputation of the selection weights 56 of each document 52 that remains in the database 50 after the editor has added and/or removed documents.
In some embodiments, the removal or addition of a document 52 to document database 50 is done manually by an editor when the editor determines that such an adjustment to the database needs to be made. In other embodiments, the editor is a computer program module that adds and deletes documents to document database 50 in accordance with some predetermined algorithm. In practice, deletion of a document 52 in document database 50 can involve setting a flag (not shown) in database 50 to a �do not use setting,� setting the selection weight of the document 52 to zero, or deleting the document 52 from document database 50 altogether.
Step 410. When an editor has deleted document 52 from database 50 and/or the look back period has elapsed (412�Yes), the selection weight 56 for each document 52 is recomputed. In a preferred embodiment, each respective document 52 is assigned a new selection weight 56 based on the number of hits to the respective document 52 during the look back period. For example, consider the case in which the number of hits to each respective document 52 is given by Table 2 above. Then, in step 410, the new selection weights for the documents 52 will be as given in Table 3.
TABLE 3 Exemplary document database 50 at step 410 Selection Weight (56) Number of Document (52) [Percentile] Indicia/Link hits (54) 52-1 350/730 Can the Dow 350 predict . . . ? 52-2 100/730 No agreements 100 52-3 80/730 Is it a bull market? 80 52-4 200/730 Title of document 4 200 52-5 0/730 Title of document 5 0 In some embodiments, counters 54 are reset in step 410 to zero.
Step 412. In step 412, a determination is made as to whether the editor wishes to include a new document 52 in document database 50. If so (412�Yes) process control passes to step 414. If not, process control passes to step 408 where each request for host web page 70 is processed as described in steps 404 through 408 above.
Step 414. In step 414, new documents 52 added to document database 50 are assigned corresponding selection weights 56. Further, the selection weights 56 of original documents 52 in document database 50 are adjusted. In preferred embodiments, each new document 52 is assigned a grace period selection weight 48 (FIG. 1) for a grace period 46. In one embodiment, grace period 46 is one look back period. In other embodiments, grace period 46 is two or more look back periods. In one embodiment of the present invention, the grace period selection weight 48 is proportional to 1/N, where N is the number of documents 52 in document database 50 after the new document has been added. For example, consider the case in which an editor decides to add a document 52-6 to document database 50 when the database is in the state illustrated in Table 4. In such preferred embodiments, document 52-6 is assigned a selection weight 56 that is ⅙. Moreover, each of the original document selection weights 56 in document database 50 are reduced by [(N−1)/N] percent, where N is six. Thus, upon completion of step 414 in this example, the status of document database 50 is given by Table 4.
Indicia/Link
(5/6) * (350/730)
Can the Dow
(5/6) * (100/730)
(5/6) * (80/730)
Is it a bull market?
(5/6) * (200/730)
Title of document 4
(5/6) * (0/730)
Title of document 5
Title of document 6
Class Designation in Automated Up-Weighting and Down-Weighting Methodologies In some embodiments of the present invention, profile management module 60 is used to determine characteristics about users that request host web page 70. In preferred embodiments, host web page 70 is available to both users that have a profile 64 in system 10 as well as users that have no such profile. In such embodiments, the determination of characteristics about users that request a host web page 70 generally applies to only those users that have a user profile 64 in user profile database 62. Methods such as those disclosed with reference to FIG. 4 are implemented for those users that do not have a user profile.
The characteristics in the user profiles 64 of users requesting host web page 70 are used to stratify the user population into classes. Then, a different set of selection weights 56 is refined for each class of users based on the popularity of documents 52 within the class. In one example, the characteristic that is used to stratify the user population into classes is geography. Each user is classified into a different geographical region (e.g., state) based on the correspondence address of the user. Then, each document 52 is assigned a set of selection weights 56, one for each geographical region. In the case where the geographical region is a state, there will be 52 selection weights 56 for each document 52 in document database 50, one for each state. Then, each respective selection weight 56 for a document 52 is refined based upon the popularity of documents 52 with users in the user class corresponding to the respective selection weight. Such refinement proceeds in accordance with the steps outlined in FIG. 4.
Referring again to FIG. 5, an exemplary user profile database 62 comprises a plurality of personal profiles 64. Each respective personal profile 64 in the plurality of personal profiles in profile database 62 uniquely represents a user of system 10. Typically, each personal profile 64 includes personal information about the user corresponding to the profile, including the user's name 500-x-1, mailing address 500-x-2, country of residence 500-x-3, and E-mail address 500-x-15. In some embodiments of the present invention, a personal profile 64 in database 62 includes personal information relating to the user corresponding to the personal profile 64. Such information can include, but is not limited to, gender 500-x-4, date of birth 500-x-5, occupation 500-x-6, any interests or hobbies 500-x-7 of the user, primary language 500-x-8 spoken by the user, political affiliation 500-x-9, education level 500-x-10, profession 500-x-11, income level 500-x-12, the academic background 500-x-13, and/or how often the user uses system 10 (frequency of use 500-x-14).
Teaser Selection for a Feature Article FIGS. 7 and 8 detail another novel application of the present invention. In order to effectively advertise a feature article on a host web page 70 without taking up too much of the available page real estate, a teaser can be used. The teaser can include the title of the feature article and/or a digital image associated with the article, or any other indicia relating to the feature article. For example, if the feature article concerns a celebrity, a recent picture of the celebrity can be shown in the teaser along with an attention grabbing synopsis of the feature article (e.g. �celebrity X arrested for drunk driving�). In the present invention, there can be a plurality of teasers for the feature article. Each time the host web page 70 is requested, one of the plurality of teasers is included in the web page based on a function of the selection weight of the teaser. In one embodiment, the higher the selection weight of a given teaser, the more likely it is that the given teaser will be selected for use in the host web page 70 when the page 70 is requested. When a user clicks on (or otherwise selects) the teaser that is on the host web page 70, the users is taken to the Uniform Resource Location (URL) where the article can be found. As in the case of document database 50, the feature article can be found in a database that houses the teasers, or in any data structure that is addressable by system 10.
In step 804, the number of times each teaser 704 is used by a user to select the feature article during the look back period is recorded in fields 706 of data structure 700. Steps 802 and 804 continue until a loop back interval has elapsed or an editor adds or removes a teaser 704 from data structure 700 (step 806�Yes). When the condition 806�Yes arises, each respective teaser 704 remaining in register 700 is assigned a new weight 708 based on the number of times a user selected the respective teaser 704 relative to the total number of times any of teaser 704 remaining in register 700 were selected by a user in the look back period (step 808). For example, in accordance with one embodiment of the invention, if teaser 704-1 was selected 100 times during a given look back period, teaser 704-2 was selected 400 times during the same look back period and the only other teaser in data structure 700, 704-3 is removed by an editor, the new weight 708-1 for teaser 704-1 will be 100/500 and the new weight 708�for teaser 704-2 will be 400/500.
In step 810, a determination is made as to whether the editor wishes to add a teaser. If so (810�Yes), process control passes to step 812 where the new teaser is assigned a grace period weight of 1/N, where N is the number of teasers 704 in data structure 700 after the new teaser has been added. Accordingly, all other teasers are reduced by [(N−1)/N] percent.
Semi-Automated Selection Weight Adjustment�Case Study: Investment Ideas In some applications, one or more editors use the document popularity results such as those illustrated in FIGS. 2 and 3 to manually revise document selection weights. FIGS. 9 and 10 illustrate. Here, the documents are investment ideas. However, the techniques described in this section can be used for any form of document. Referring to FIG. 9, a data structure 900 includes a header 904 for each investment idea. In some embodiments, each header 904 includes HTML and/or other forms of content that is displayed on host web page 70 when the investment idea corresponding to the header is selected for inclusion in the web page. In some embodiments, header 904 includes a URL or other form of pointer to the corresponding investment idea. In some embodiments (not shown) each investment idea is stored in data structure 900.
In step 1006, the number of times each investment idea is selected by a user during a look back period is recorded in fields 706 of data structure 700. In some embodiments such numbers are tracked in percentage form rather than absolute form. Steps 1004 and 1006 continue until a loop back interval has elapsed or an editor adds or removes an investment idea to data structure 900 (step 1008�Yes).
When step 1008�Yes arises, each respective investment idea remaining in register 700 can be assigned a new weight 908 in accordance with steps 1010 through 1018. For each respective investment idea steps 1012 through 1018 are performed. In step 1012 a determination is made as to whether the selection weight for an investment idea matches the percentage of times that the investment idea was selected by a users. To make such a determination, investment weights are expressed in percentage form. Table 5 illustrates.
TABLE 5 State information at steps 1010/1012 Selection Number of times selected during Investment Idea Weight 708 look back periods expressed in (No.) [Percentile] percentile form 1 50 60 2 10 8 3 10 12 4 10 14 5 10 6 Table 5 illustrates how investment idea number 1 was weighted such that it would be selected for inclusion in an instance of host web page 70 fifty percent of the time. However, during the look back period, investment idea number 1 was selected by users from host web page 70 sixty percent of the time. This suggests that the selection weight for investment idea number 1 should be increased to sixty percent (1012�Yes, 1014). In contrast, investment idea number five has a selection weight percentile of 10 percent but only receives six percent of the investment idea requests during a given time period. This suggests that the selection weight for investment idea number five should be decreased (1014�No, 1016).
CONCLUSION Many modifications and variations of this invention can be made without departing from its spirit and scope, as will be apparent to those skilled in the art. Reference has been made to certain computer systems. However, the present invention contemplates implementation of the inventive methods on any form of technology, whether currently existing or to be developed in the future, that implements electronic social networking. The specific embodiments described herein are offered by way of example only, and the invention is to be limited only by the terms of the appended claims, along with the full scope of equivalents to which such claims are entitled.
Patent CitationsCited PatentFiling datePublication dateApplicantTitleUS6163778 *Feb 6, 1998Dec 19, 2000Sun Microsystems, Inc.Probabilistic web link viability marker and web page ratingsUS6643612 *Jun 28, 2001Nov 4, 2003Atrica Ireland LimitedMechanism and protocol for per connection based service level agreement measurementUS6718324 *Jan 30, 2003Apr 6, 2004International Business Machines CorporationMetadata search results ranking systemUS7031961 *Dec 4, 2000Apr 18, 2006Google, Inc.System and method for searching and recommending objects from a categorically organized information repositoryUS20020075302 *Dec 15, 2000Jun 20, 2002Xerox CorporationMethod of displaying hypertext based on a prominence ratingUS20040006747 *Jun 25, 2003Jan 8, 2004Tyler Joseph C.Electronic publishing system and methodUS20050060297 *Sep 16, 2003Mar 17, 2005Microsoft CorporationSystems and methods for ranking documents based upon structurally interrelated informationUS20050071741 *Dec 31, 2003Mar 31, 2005Anurag AcharyaInformation retrieval based on historical dataUS20050131762 *Dec 31, 2003Jun 16, 2005Krishna BharatGenerating user information for use in targeted advertising* Cited by examinerReferenced byCiting PatentFiling datePublication dateApplicantTitleUS8015479 *Nov 8, 2006Sep 6, 2011Canon Kabushiki KaishaInformation processing apparatus, electronic document processing method, and storage medium* Cited by examinerClassifications U.S. Classification1/1, 715/255, 707/999.005International ClassificationG06F17/30, G06F7/00Cooperative ClassificationY10S707/99935, G06Q30/0201, G06F17/3089European ClassificationG06Q30/0201, G06F17/30W7Legal EventsDateCodeEventDescriptionSep 28, 2012FPAYFee paymentYear of fee payment: 4Jul 22, 2004ASAssignmentOwner name: YAHOO! INC., CALIFORNIAFree format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:FRIEDL, JEFFREY E. F.;HARTNACK, KATHLEEN L.;REEL/FRAME:015616/0554;SIGNING DATES FROM 20040623 TO 20040719RotateOriginal ImageGoogle Home - Sitemap - USPTO Bulk Downloads - Privacy Policy - Terms of Service - About Google Patents - Send FeedbackData provided by IFI CLAIMS Patent Services©2012 Google