INTERESTINGNESS RECOMMENDATIONS IN A COMPUTING ADVICE FACILITY
The present disclosure provides a recommendation to a user through a computer-based advice facility to rank search results by performing steps of receiving a search request from a user; retrieving a list of search results; ascertaining preferences of the user to create a taste and preference profile for the user; matching the user to other users with similar taste and preference profiles; and providing the search results to the user, wherein the search results are ranked according to the matched results selected by other users with similar taste and preference profiles. In embodiments, tastes and preferences of a user may be based on information inferred from a user's activity on a social network or augmented through other users that have a connection to the user through a social network.
1 .- 20 . (canceled)
21 . A computer-implemented method comprising:
receiving one or more search query terms submitted by a particular user;
retrieving a list of search results based on the search query terms;
accessing user preference profile information identifying one or more preferences of the particular user;
ranking the list of search results, based on the user preference profile information, wherein a first search result matching the preferences of the particular user is ranked higher in the ranked list in comparison to a second search result that does not match the preferences of the particular user; and
providing the ranked list of search results to the particular user.
22 . The method of claim 21 , further comprising:
identifying the preferences of the particular user; and
generating the user preference profile information identifying the preferences of the particular user.
23 . The method of claim 21 , wherein the preferences of the particular user are identified by analyzing user actions of the particular user on an online social network.
24 . The method of claim 23 , wherein the preferences of the particular user are identified based on other users that have a connection to the particular user through the online social network.
25 . The method of claim 21 , wherein the preferences of the particular user are identified based on previous search result selections of the particular user.
26 . The method of claim 21 , wherein the preferences of the particular user are identified by crawling, from a third party website, information describing the preferences of the particular user.
27 . The method of claim 21 , wherein the preferences of the particular user are identified from online sources indicating location-based behavior of the particular user.
28 . The method of claim 21 , wherein the search results describe at least one product.
29 . A non-transitory machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform operations comprising:
receiving one or more search query terms submitted by a particular user;
retrieving a list of search results based on the search query terms;
accessing user preference profile information identifying one or more preferences of the particular user;
ranking the list of search results, based on the user preference profile information, wherein a first search result matching the preferences of the particular user is ranked higher in the ranked list in comparison to a second search result that does not match the preferences of the particular user; and
providing the ranked list of search results to the particular user.
30 . The storage medium of claim 29 , wherein the operations further comprise:
identifying the preferences of the particular user; and
generating the user preference profile information identifying the preferences of the particular user.
31 . The storage medium of claim 29 , wherein the preferences of the particular user are identified by analyzing user actions of the particular user on an online social network.
32 . The storage medium of claim 31 , wherein the preferences of the particular user are identified based on other users that have a connection to the particular user through the online social network.
33 . The storage medium of claim 29 , wherein the preferences of the particular user are identified based on previous search result selections of the particular user.
34 . The storage medium of claim 29 , wherein the preferences of the particular user are identified by crawling, from a third party website, information describing the preferences of the particular user.
35 . The storage medium of claim 29 , wherein the preferences of the particular user are identified from online sources indicating location-based behavior of the particular user.
36 . A system comprising:
a machine including a memory and at least one processor; and
a recommendation module, executable by the machine, configured to:
receive one or more search query terms submitted by a particular user;
retrieve a list of search results based on the search query terms;
access user preference profile information identifying one or more preferences of the particular user;
rank the list of search results, based on the user preference profile information, wherein a first search result matching the preferences of the particular user is ranked
higher in the ranked list in comparison to a second search result that does not match the preferences of the particular user; and
provide the ranked list of search results to the particular user.
37 . The system of claim 36 , wherein the recommendation module is further configured to:
identify the preferences of the particular user; and
generate the user preference profile information identifying the preferences of the particular user.
38 . The system of claim 36 , wherein the preferences of the particular user are identified by analyzing user actions of the particular user on an online social network.
39 . The system of claim 38 , wherein the preferences of the particular user are identified based on other users that have a connection to the particular user through the online social network.
40 . The system of claim 36 , wherein the preferences of the particular user are identified based on previous search result selections of the particular user.