Method and System for Discovery of User Unknown Interests Based on Supplemental Content

1. A method for identifying content for a user, the method implemented on a machine having at least one processor, storage, and a communication interface connected to a network, the method comprising: retrieving information related to a user from a user profile, wherein the information indicates one or more known interests of the user; identifying at least one known interest of the user based on the information; determining one or more supplemental interests with respect to each of the identified at least one known interest of the user, where the one or more supplemental interests do not overlap with the one or more known interests of the user; identifying supplemental content associated with the one or more supplemental interests with respect to each of the identified at least one known interest of the user; ranking each piece of content in the supplemental content; and selecting at least one piece of content in the supplemental content based on the ranking, wherein the selected at least one piece of supplemental content associated with the one or more supplemental interests is used to discover unknown interest of the user.

2. The method of claim 1 , further comprising: identifying relatedness between each piece of content in the supplemental content and its corresponding supplemental interest; and outputting the selected content from the supplemental content.

3. The method of claim 1 further comprising: randomly obtaining content; and adding the randomly obtained content to the supplemental content.

4. The method of claim 1 further comprising filtering the ranked content in the supplemental content based on a criteria.

5. The method of claim 1 , wherein step of determining comprises: estimating a metric for each of a plurality of candidate supplemental interests; and selecting the one or more supplemental interests based on their respective metrics with respect to a threshold.

6. The method of claim 5 , wherein the metric includes at least one of: a distance between two interests in a content taxonomy; a co-occurrence of two interests in a collection of content; a co-occurrence of two interests in a set of user profiles; a co-occurrence of two interests in a set of user sessions; and any combination thereof.

7. The method of claim 1 , wherein the unknown interest of the user is discovered based on interaction between the user and the selected at least one piece of supplemental content.

8. A system for identifying unknown user content, the system comprising: a retrieval unit for retrieving information related to a user from a user profile, wherein the information indicates one or more known interests of the user; an interest analyzer for identifying at least one known interest of the user based on the information; a supplemental interest identifier for determining one or more supplemental interests with respect to each of the identified at least one known interest of the user, where the one or more supplemental interests do not overlap with the one or more known interests of the user; a supplemental content identifier for identifying supplemental content associated with the one or more supplemental interests with respect to each of the identified at least one known interest of the user; a ranking unit for ranking each piece of content in the supplemental content; and a selector for selecting at least one piece of content in the supplemental content based on the ranking, wherein the selected at least one piece of supplemental content associated with the one or more supplemental interests is used to discover unknown interest of the user.

9. The system of claim 8 , further comprising: a supplemental weighting unit for identifying relatedness between each piece of content in the supplemental content and its corresponding supplemental interest; and an output for outputting the selected content from the supplemental content.

10. The system of claim 8 , further comprising a random content selector configured for: randomly obtaining content; and adding the randomly obtained content to the supplemental content.

11. The system of claim 8 , wherein the supplemental interest identifier is further configured for: estimating a metric for each of a plurality of candidate supplemental interests; and selecting the one or more supplemental interests based on their respective metrics with respect to a threshold.

12. The system of claim 11 , wherein the metric includes at least one of: a distance between two interests in a content taxonomy; a co-occurrence of two interests in a collection of content; a co-occurrence of two interests in a set of user profiles; a co-occurrence of two interests in a set of user sessions; and any combination thereof.

13. The system of claim 8 , wherein the unknown interest of the user is discovered based on interaction between the user and the selected at least one piece of supplemental content.

14. The system of claim 8 , wherein the ranked content in the supplemental content is filtered based on a criteria.

15. A non-transitory machine-readable medium having recorded thereon information for identifying unknown user interest, wherein the information, when read by a machine, causes the machine to perform the steps of: retrieving information related to a user from a user profile, wherein the information indicates one or more known interests of the user; identifying at least one known interest of the user based on the information; determining one or more supplemental interests with respect to each of the identified at least one known interest of the user, where the one or more supplemental interests do not overlap with the one or more known interests of the user; identifying supplemental content associated with the one or more supplemental interests with respect to each of the identified at least one known interest of the user; ranking each piece of content in the supplemental content; and selecting at least one piece of content in the supplemental content based on the ranking, wherein the selected at least one piece of supplemental content associated with the one or more supplemental interests is used to discover unknown interest of the user.

16. The non-transitory machine-readable medium of claim 15 , wherein the information, when read by the machine, further causes the machine to perform the steps of: identifying relatedness between each piece of content in the supplemental content and its corresponding supplemental interest; and outputting the selected content from the supplemental content.

17. The non-transitory machine-readable medium of claim 15 , wherein the information, when read by the machine, further causes the machine to perform the steps of: randomly obtaining content; and adding the randomly obtained content to the supplemental content.

18. The non-transitory machine-readable medium of claim 15 , wherein step of determining comprises: estimating a metric for each of a plurality of candidate supplemental interests; and selecting the one or more supplemental interests based on their respective metrics with respect to a threshold.

19. The non-transitory machine-readable medium of claim 18 , wherein the metric includes at least one of: a distance between two interests in a content taxonomy; a co-occurrence of two interests in a collection of content; a co-occurrence of two interests in a set of user profiles; a co-occurrence of two interests in a set of user sessions; and any combination thereof.

20. The non-transitory machine-readable medium of claim 15 , wherein the unknown interest of the user is discovered based on interaction between the user and the selected at least one piece of supplemental content.