Source: https://patents.google.com/patent/US9542453B1/en
Timestamp: 2019-05-22 01:22:51
Document Index: 518750701

Matched Legal Cases: ['Application No. 60', 'Application No. 2573672', 'Application No. 200580030640', 'Application No. 200780019748', 'Application No. 200780019748', 'Application No. 200780019748', 'Application No. 05771572', 'Application No. 07759892', 'Application No. 200580030640', 'Application No. 2007', 'Application No. 2007']

US9542453B1 - Systems and methods for promoting search results based on personal information - Google Patents
Systems and methods for promoting search results based on personal information Download PDF
US9542453B1
US9542453B1 US14/821,297 US201514821297A US9542453B1 US 9542453 B1 US9542453 B1 US 9542453B1 US 201514821297 A US201514821297 A US 201514821297A US 9542453 B1 US9542453 B1 US 9542453B1
US14/821,297
2004-07-13 Priority to US10/890,854 priority Critical patent/US7693827B2/en
2005-03-18 Priority to US11/084,379 priority patent/US7979501B1/en
2005-12-01 Priority to US29290505A priority
2006-03-30 Priority to US11/394,620 priority patent/US8078607B2/en
2007-03-13 Priority to US89467307P priority
2007-08-28 Priority to US11/846,346 priority patent/US8620915B1/en
2013-12-06 Priority to US14/099,854 priority patent/US9116963B2/en
2015-08-07 Priority to US14/821,297 priority patent/US9542453B1/en
2015-08-07 Application filed by Google LLC filed Critical Google LLC
2017-01-10 Publication of US9542453B1 publication Critical patent/US9542453B1/en
This application is a continuation of, and claims priority to, U.S. patent application Ser. No. 14/099,854, filed on Dec. 6, 2013, now U.S. Pat. No. 9,116,963, entitled, “Systems and Methods for Promoting Personalized Search Results Based on Personal Information,” which is a continuation of U.S. patent application Ser. No. 11/846,346, filed on Aug. 28, 2007, now U.S. Pat. No. 8,620,915, entitled “Systems and Methods for Promoting Personalized Search Results Based on Personal Information,” which claims priority to U.S. Provisional Application No. 60/894,672, filed on Mar. 13, 2007, titled “Systems and Methods for Promoting Search Results in Personalized Search,” and 60/894,673, filed on Mar. 13, 2007, titled “Systems and Methods for Demoting Search Results in Personalized Search,” all of which are hereby incorporated by reference in their entirety.
To serve a list of search results best fit for a particular user, the user's user profile should capture the user's search interests when the user submits a search query. Besides search queries, a user's search interests may be reflected by the websites, domains, particular URLs, or other classification schemes of web pages that the user visits frequently. For example, a user who often visits consumer electronics websites should probably have a user profile that boosts webpages related to consumer electronic products while a user who pays frequent visits to online grocery stores should probably have a user profile that promotes webpages relating to grocery stores and cooking. In most cases, a user's search interests vary over time. Accordingly, the user's user profile should be updated from time to time (e.g., periodically) to keep track of the user's current search interests.
The value of “f1( )” increases with an increase of the “click_count” attribute, and decreases with a decrease of the “click_count” attribute, which means that a search result that receives more user selections is given more preference. Similarly, the value of “f2( )” increases with an increase of the “time_span” attribute, and decreases with a decrease in the “time_span” attribute, which means that a series of user selections of a search result over a longer time period is more likely to reflect the user's long-term search interest. But the value of “f3( )” increases with a decrease of the “time_decay” attribute, and decreases with an increase of the “time_delay” attribute, which means that a series of user selections of a search result that is more recent is more likely to reflect the user's current search interest. Each of the functions f1, f2, f3 may be linear or non-linear. One skilled in the art will find many other ways of calculating the popularity metric for a search result using the attributes or the like.
average_popularity_metric(A,B)=Average(popularity_metric(B) in UP-1, . . . , popularity metric(B) in UP-S),
identifying search results associated with the search query;
identifying a set of user-preferred search results that includes search results in a search history of the user, wherein each of the user-preferred search results has been previously selected by the user for at least a predefined minimum number of times;
identifying in the search results, one or more search results, each of which is associated with a respective user-preferred search result;
ordering the search results based at least in part on a popularity metric associated with each of the identified search results, wherein the popularity metric is a function of one or more parameters including at least one parameter that is a time span period from the user's most remote selection of the respective user-preferred search result to the user's most recent selection of the respective user-preferred search result; and
5. The method of claim 1, further comprising receiving the search history of the user from one or more client devices associated with the user.
6. A computer system for producing personalized search results, comprising:
instructions for identifying search results associated with the search query;
instructions for identifying a set of user-preferred search results that includes search results in a search history of the user, wherein each of the user-preferred search results has been previously selected by the user for at least a predefined minimum number of times;
instructions for identifying in the search results, one or more search results, each of which is associated with a respective user-preferred search results result;
instructions for ordering the search results based at least in part on a popularity metric associated with each of the identified search results, wherein the popularity metric is a function of one or more parameters including at least one parameter that is a time span period from the user's most remote selection of the respective user-preferred search result to the user's most recent selection of the respective user-preferred search result; and
instructions for providing the ordered search results to the user.
7. The computer system of claim 6, wherein each of the user-preferred search results has been selected by the user for at least the predefined minimum number of times spanning a time period having at least a predefined minimum duration.
8. The computer system of claim 6, wherein the predefined minimum number of times is a positive integer greater than 1.
9. The computer system of claim 6, wherein previous selection of a search result by the user comprises clicking on the search result and staying on a corresponding document for at least a predefined minimum duration.
10. The computer system of claim 6, the one or more programs further including instructions for receiving the search history of the user from one or more client devices associated with the user.
11. A computer-implemented method performed at a server system having one or more processors and memory, the method comprising:
identifying a user profile associated with the user, wherein the user profile includes a set of user-preferred search results that is determined, at least in part, by:
identifying a set of candidate search results in a search history of the user, wherein each of the candidate search results has been selected by the user for at least a predefined minimum number of times;
determining a popularity metric for each of the candidate search results; and
selecting a subset of the candidate search results whose associated popularity metrics exceed a predefined threshold as the set of user-preferred search results;
identifying in the search results, one or more search results that are associated with at least one of the user-preferred search results;
ordering the search results based at least in part on the identification, in the search results, of the one or more search results that are associated with at least one of the user-preferred search results; and
12. The method of claim 11, wherein the ordering is based at least in part on a function of a popularity metric associated with each of the identified search results.
13. The method of claim 11, wherein each of the candidate search results has been selected by the user for at least the predefined minimum number of times during a time period having at least a predefined minimum duration.
14. The method of claim 11, wherein the popularity metric of a candidate search result is a function of one or more parameters including at least one parameter which is a time span period from the user's most remote selection of the candidate search result to the user's most recent selection of the candidate search result.
15. The method of claim 11, wherein the popularity metric of a candidate search result is determined by:
determining a model predicting a likelihood of a user selection of a search result using multiple users' search histories; and
applying the model to the user's search history to generate the popularity metric of the candidate search result.
16. The method of claim 15, wherein the model is determined by:
determining as the model a set of coefficients from the profile, wherein the set of coefficients, when applied to a set of search results associated from a specific user's search history, is configured to predict the likelihood of the specific user's selection of each of the search results in the future.
17. The method of claim 11, wherein the popularity metric of a candidate search result is a function of two or more parameters, wherein the parameters include:
a time span period from the user's most remote selection of the candidate search result to the user's most recent selection of the candidate search result; and
a time decay period from the user's most recent selection of the candidate search result to present.
18. The method of claim 11, further comprising receiving the search history of the user from one or more client devices associated with the user.
19. A computer system for producing personalized search results, comprising:
instructions for identifying a user profile associated with the user, wherein the user profile includes a set of user-preferred search results determined, at least in part, by:
instructions for identifying a set of candidate search results in a search history of the user, wherein each of the candidate search results has been selected by the user for at least a predefined minimum number of times;
instructions for determining a popularity metric for each of the candidate search results; and
instructions for selecting a subset of the candidate search results whose associated popularity metrics exceed a predefined threshold as the set of user-preferred search results;
instructions for identifying in the search results, one or more search results that are associated with at least one of the user-preferred search results;
instructions for ordering the search results based at least in part on the identification, in the search results, of the one or more search results that are associated with at least one of the user-preferred search results; and
instructions for providing the ordered list of search results to the user.
20. The computer system of claim 19, wherein the ordering is based at least in part on a function of a popularity metric associated with each of the identified search results.
21. The computer system of claim 19, wherein each of the candidate search results has been selected by the user for at least the predefined minimum number of times during a time period having at least a predefined minimum duration.
22. The computer system of claim 19, wherein the popularity metric of a candidate search result is a function of one or more parameters including at least one parameter which is a time span period from the user's most remote selection of the candidate search result to the user's most recent selection of the candidate search result.
23. The computer system of claim 19, wherein the instructions for determining the popularity metric of a candidate search result further include:
instructions for determining a model predicting a likelihood of a user selection of a search result using multiple users' search histories; and
instructions for applying the model to the user's search history to generate the popularity metric of the candidate search result.
24. The computer system of claim 23, wherein the instructions for determining the model further include:
instructions for determining as the model a set of coefficients from the profile, wherein the set of coefficients, when applied to a set of search results associated from a specific user's search history, is configured to predict the likelihood of the specific user's selection of each of the search results in the future.
25. The computer system of claim 19, wherein the predefined number of times is at least two.
26. The computer system of claim 19, wherein the popularity metric of a candidate search result is a function of two or more parameters, wherein the parameters include:
27. The computer system of claim 19, the one or more programs further including instructions for receiving the search history of the user from one or more client devices associated with the user.
US14/821,297 2003-09-30 2015-08-07 Systems and methods for promoting search results based on personal information Active US9542453B1 (en)
US10/890,854 US7693827B2 (en) 2003-09-30 2004-07-13 Personalization of placed content ordering in search results
US11/084,379 US7979501B1 (en) 2004-08-06 2005-03-18 Enhanced message display
US29290505A true 2005-12-01 2005-12-01
US11/394,620 US8078607B2 (en) 2006-03-30 2006-03-30 Generating website profiles based on queries from webistes and user activities on the search results
US11/846,346 US8620915B1 (en) 2007-03-13 2007-08-28 Systems and methods for promoting personalized search results based on personal information
US14/099,854 US9116963B2 (en) 2007-03-13 2013-12-06 Systems and methods for promoting personalized search results based on personal information
US14/821,297 US9542453B1 (en) 2004-07-13 2015-08-07 Systems and methods for promoting search results based on personal information
US14/099,854 Continuation US9116963B2 (en) 2007-03-13 2013-12-06 Systems and methods for promoting personalized search results based on personal information
US9542453B1 true US9542453B1 (en) 2017-01-10
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