Collaborative topic regression for online recommender systems: An online and Bayesian approach

Collaborative topic regression for online recommender systems: An online and Bayesian approach

Collaborative Topic Regression (CTR) combines ideas of probabilistic matrix factorization (PMF) and topic modeling (such as LDA) for recommender systems, which has gained increasing success in many applications. Despite enjoying many advantages, the existing Batch Decoupled Inference algorithm for t...

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書目詳細資料
Main Authors:	LIU, Chenghao, JIN, Tao, HOI, Steven C. H., ZHAO, Peilin, SUN, Jianling
格式:	text
語言:	English
出版:	Institutional Knowledge at Singapore Management University 2017
主題:	Topic modeling Online learning Recommender systems Collaborative filtering Databases and Information Systems Theory and Algorithms
在線閱讀:	https://ink.library.smu.edu.sg/sis_research/3703 https://ink.library.smu.edu.sg/context/sis_research/article/4705/viewcontent/CollaborativeTopicRegressionOnlineRecomSys_2017.pdf
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!
機構:	Singapore Management University
語言:	English

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