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