发明名称 |
Recommendations in a computing advice facility |
摘要 |
According to various embodiments, a ratings matrix including matrix values is generated, each row of the ratings matrix identifying one of a plurality of users, each column of the ratings matrix identifying one of a plurality of items, and each of the matrix values corresponding to a known affinity rating describing a degree of affinity associated with one of the users and one of the items. The ratings matrix may include a missing entry representing an unknown affinity rating. According to various embodiments, a revised ratings matrix is generated by factoring the ratings matrix into a user matrix and an item matrix, the revised ratings matrix being the product of the user matrix and the item matrix and including at least one entry representing a predicted affinity rating in place of the missing entry. |
申请公布号 |
US9009096(B2) |
申请公布日期 |
2015.04.14 |
申请号 |
US201213547893 |
申请日期 |
2012.07.12 |
申请人 |
eBay Inc. |
发明人 |
Pinckney Thomas;Dixon Christopher;Gattis Matthew Ryan |
分类号 |
G06F9/44;G06N7/02;G06N7/06;G06N5/04;G06F17/30 |
主分类号 |
G06F9/44 |
代理机构 |
Schwegman Lundberg & Woessner, P.A. |
代理人 |
Schwegman Lundberg & Woessner, P.A. |
主权项 |
1. A method comprising:
generating a ratings matrix including matrix values, each row of the ratings matrix identifying one of a plurality of users, each column of the ratings matrix identifying one of a plurality of items, and each of the matrix values corresponding to a known affinity rating describing a degree of affinity associated with one of the users and one of the items, wherein the ratings matrix includes a missing entry representing an unknown affinity rating; generating, using one or more processors, a revised ratings matrix by factoring the ratings matrix into a user matrix and an item matrix, the revised ratings matrix being the product of the user matrix and the item matrix and including at least one entry representing a predicted affinity rating in place of the missing entry; estimating a confidence value associated with at least a portion of the known affinity ratings in the ratings matrix; generating a confidence matrix that includes the confidence values; estimating a probability that a specific user had an opportunity to rate a specific item, the specific user and the specific item being associated with a missing affinity rating in the ratings matrix; replacing the missing affinity rating in the ratings matrix with a low affinity rating; and inserting a confidence value associated with the specific user and the specific item in the confidence matrix, the confidence value having a value equal to the probability. |
地址 |
San Jose CA US |