Method and system for cold-start item recommendation

Patent metadata

Field	Value
Publication number	US-2016110646-A1
Application number	US-201414519273-A
Country	US
Kind code	A1
Filing date	Oct 21, 2014
Priority date	Oct 21, 2014
Publication date	Apr 21, 2016
Grant date	—

Abstract

Method, system, and programs for estimating interests of a plurality of users with respect to a new piece of information are disclosed. In one example, historical interests of the plurality of users are obtained with respect to one or more existing pieces of information. One or more users are selected from the plurality of users. Historical interests of the one or more users can minimize an objective function over the plurality of users. Interests of the one or more users are obtained with respect to the new piece of information. Estimated interests of the plurality of users are generated with respect to the new piece of information based on the obtained interests of the one or more users.

First claim

We claim:

1 . A method, implemented on a machine having at least one processor, storage, and a communication platform connected to a network for estimating interests of a plurality of users with respect to a new piece of information, comprising:
obtaining historical interests of the plurality of users with respect to one or more existing pieces of information; selecting one or more users from the plurality of users, wherein historical interests of the one or more users minimize an objective function over the plurality of users; obtaining interests of the one or more users with respect to the new piece of information; and generating estimated interests of the plurality of users with respect to the new piece of information based on the obtained interests of the one or more users.

2 . The method of claim 1 , wherein quantity of the selected one or more users is a predetermined number.

3 . The method of claim 1 , wherein the objective function represents an expected mean square error between the estimated interests and real interests of the plurality of users with respect to the new piece of information.

4 . The method of claim 1 , wherein selecting one or more users from the plurality of users comprises:
generating a vector for each of the plurality of users, wherein the vector represents historical interests of the user; determining a plurality of user sets, wherein each user set comprises a same predetermined number of users in the plurality of users; generating a plurality of function values by calculating the objective function based on vectors for each of the plurality of user sets; and selecting one of the plurality of user sets so that the function value generated based on the selected user set is least among the plurality of function values.

5 . The method of claim 1 , wherein selecting one or more users from the plurality of users comprises:
generating a vector for each of the plurality of users, wherein the vector represents historical interests of the user; determining a user set which initially comprises the plurality of users; generating a matrix which initially comprises a plurality of columns, wherein each column of the matrix corresponds to a generated vector for one of the users in the user set; generating a plurality of candidate matrices each of which corresponding to a user in the user set and generated by removing the column corresponding to the user from the matrix; generating a plurality of function values by calculating the objective function based on each of the plurality of candidate matrices; selecting one of the plurality of candidate matrices so that the function value generated based on the selected candidate matrix is least among the plurality of function values; updating the matrix with the selected candidate matrix; and updating the user set by removing the user corresponding to the selected candidate matrix from the user set.

6 . The method of claim 1 , wherein the estimated interests of the plurality of users are generated based on a least squares model.

7 . The method of claim 1 , further comprising:
identifying a user other than the plurality of users; and estimating interest of the user based on the obtained interests of the one or more users.

8 . A system, having at least one processor, storage, and a communication platform connected to a network for estimating interests of a plurality of users with respect to a new piece of information, comprising:
a user interest retriever configured to obtain historical interests of the plurality of users with respect to one or more existing pieces of information; a reviewer selection unit configured to select one or more users from the plurality of users, wherein historical interests of the one or more users minimize an objective function over the plurality of users; a review receiver configured to obtain interests of the one or more users with respect to the new piece of information; and a user interest estimation unit configured to generate estimated interests of the plurality of users with respect to the new piece of information based on the obtained interests of the one or more users.

9 . The system of claim 8 , wherein quantity of the selected one or more users is a predetermined number.

10 . The system of claim 8 , wherein the objective function represents an expected mean square error between the estimated interests and real interests of the plurality of users with respect to the new piece of information.

11 . The system of claim 8 , wherein the reviewer selection unit comprises:
a reviewer selection controller configured to generate a vector for each of the plurality of users, wherein the vector represents historical interests of the user; a reviewer determiner configured to determine a plurality of user sets, wherein each user set comprises a same predetermined number of users in the plurality of users; and an objective function calculation unit configured to generate a plurality of function values by calculating the objective function based on vectors for each of the plurality of user sets, wherein the reviewer determiner is further configured to select one of the plurality of user sets so that the function value generated based on the selected user set is least among the plurality of function values.

12 . The system of claim 8 , wherein the reviewer selection unit comprises:
a reviewer selection controller configured to generate a vector for each of the plurality of users, wherein the vector represents historical interests of the user; a reviewer determiner configured to determine a user set which initially comprises the plurality of users; and an objective function calculation unit configured to generate a matrix which initially comprises a plurality of columns, wherein each column of the matrix corresponds to a generated vector for one of the users in the user set, wherein the reviewer determiner and the objective function calculation unit are further configured to
generate a plurality of candidate matrices each of which corresponding to a user in the user set and generated by removing the column corresponding to the user from the matrix,
generate a plurality of function values by calculating the objective function based on each of the plurality of candidate matrices,
select one of the plurality of candidate matrices so that the function value generated based on the selected candidate matrix is least among the plurality of function values,
update the matrix with the selected candidate matrix, and
update the user set by removing the user corresponding to the selected candidate matrix from the user set.

13 . The system of claim 8 , wherein the estimated interests of the plurality of users are generated based on a least squares model.

14 . The system of claim 8 , wherein the user interest estimation unit is further configured to:
identify a user other than the plurality of users; and estimate interest of the user based on the obtained interests of the one or more users.

15 . A machine-readable tangible and non-transitory medium having information recorded thereon for estimating interests of a plurality of users with respect to a new piece of information, wherein the information, when read by the machine, causes the machine to perform the following:
obtaining historical interests of the plurality of users with respect to one or more existing pieces of information; selecting one or more users from the plurality of users, wherein historical interests of the one or more users minimize an objective function over the plurality of users; obtaining interests of

Assignees

• Yahoo Inc

Inventors

• Somekh Oren Shlomo
• Golan Shahar
• Golbandi Nadav
• Karnin Zohar
• Rokhlenko Oleg
• Anava Oren
• Lempel Ronny

Classifications

• G06N7/01

  Probabilistic graphical models, e.g. probabilistic networks · CPC title

• G06N5/04 Primary

  Inference or reasoning models · CPC title

• G06Q30/0631

  Recommending goods or services · CPC title

• G06N20/00 Primary

  Machine learning · CPC title