Systems and methods for promoting search results based on personal information

1. A computer-implemented method performed at a server system having one or more processors and memory, the method comprising:

receiving a search query from a user;

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

providing the ordered search results to the user.

2. The method of claim 1 , 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.

3. The method of claim 1 , wherein the predefined minimum number of times is a positive integer greater than 1.

4. The method of claim 1 , 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.

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:

memory;

one or more processors;

one or more programs stored in the memory and configured for execution by the one or more processors, the one or more programs including:

instructions for receiving a search query from a user;

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:

receiving a search query from a user;

identifying search results associated with the search query;

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

providing the ordered search results to the user.

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:

generating a profile that characterizes the multiple users' behaviors over multiple search results in the multiple users' search histories; and

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:

memory;

one or more processors;

one or more programs stored in the memory and configured for execution by the one or more processors, the one or more programs including:

instructions for receiving a search query from a user;

instructions for identifying search results associated with the search query;

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 generating a profile that characterizes the multiple users' behaviors over multiple search results in the multiple users' search histories; and

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:

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.

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.