发明名称 ALMOST ONLINE LARGE SCALE COLLABORATIVE FILTERING BASED RECOMMENDATION SYSTEM
摘要 A method for adjusting one or more parameters associated with a model. The method comprises obtaining, from a first source, first information related to activity of a user. The method further comprises adjusting one or more parameters associated with a model based on the first information collected within a first length of time, and obtaining, from a second source, second information related to activity of the user. The method further comprises adjusting the one or more parameters associated with the model based on the second information collected within a second length of time and a measure indicative of performance of the model, wherein the second length of time is larger than the first length of time.
申请公布号 US2014280251(A1) 申请公布日期 2014.09.18
申请号 US201314123321 申请日期 2013.03.15
申请人 YAHOO! Inc. 发明人 Somekh Oren Shlomo;Golbandi Nadav;Rokhlenko Oleg;Lempel Ronny
分类号 G06F17/30 主分类号 G06F17/30
代理机构 代理人
主权项 1. A method implemented on a machine having at least one processor, a storage, and a communication platform for adjusting one or more parameters associated with a model, comprising: obtaining, from a first source, first information related to activity of a user; adjusting one or more parameters associated with a model based on the first information obtained within a first time period having a first length of time; obtaining, from a second source, second information related to activity of the use; and adjusting at least the one or more parameters associated with the model based on the second information obtained within a second time period having a second length of time and a measure indicative of performance of the model, wherein the model is used to determine an affiliation between the user and content, and the second length of time is larger than the first length of time.
地址 Sunnyvale CA US