{"title":"Modeling Dynamic User Interests: A Neural Matrix Factorization Approach","authors":"Paramveer S. Dhillon, Sinan Aral","doi":"10.1287/mksc.2021.1293","DOIUrl":null,"url":null,"abstract":"We propose an interpretable model that combines the simplicity of matrix factorization with the flexibility of neural networks to model evolving user interests by efficiently extracting nonlinear patterns from massive text data collections.","PeriodicalId":423558,"journal":{"name":"Mark. Sci.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mark. Sci.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1287/mksc.2021.1293","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
We propose an interpretable model that combines the simplicity of matrix factorization with the flexibility of neural networks to model evolving user interests by efficiently extracting nonlinear patterns from massive text data collections.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
