{"title":"动态用户兴趣建模:神经矩阵分解方法","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":"{\"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}","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}
Modeling Dynamic User Interests: A Neural Matrix Factorization Approach
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.
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