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Coupled Topic Model for Collaborative Filtering With User-Generated Content
Wu, Shu1; Guo, Weiyu2; Xu, Song3; Huang, Yongzhen1; Wang, Liang1; Tan, Tieniu1
Source PublicationIEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS
2016-12-01
Volume46Issue:6Pages:908-920
SubtypeArticle
AbstractThe user-generated content (UGC) is a type of dyadic information that provides description of the interaction between users and items (such as rating, purchasing, etc.). Most conventional methods incorporate either a user profile or the item description, which cannot well utilize this kind of content information. Some other works jointly consider user ratings and reviews, but they are based on the factorization technique and have difficulty in providing explanations on generated recommendations. In this study, a coupled topicmodel (CoTM) for recommendation with UGCis developed. By combiningUGCand ratings, themethod discussed in this study captures both the content-based preferences and collaborative preferences and, thus, can explain both the user and item latent spaces using the topics discovered from the UGC. The learned topics in CoTM can also serve as proper explanations for the generated recommendations. Experimental results show that the proposed CoTM model yields significant improvements over the compared competitive methods on two typical datasets, that is, MovieLens-10M and Citation-network V1. The topics discovered by CoTM can be used not only to illustrate the topic distributions of users and items, but also to explain the generated user-item recommendations.
KeywordCollaborative Filtering (Cf) Recommender Systems (Rs) Topic Model User-generated Content (Ugc)
WOS HeadingsScience & Technology ; Technology
DOI10.1109/THMS.2016.2586480
WOS KeywordSYSTEMS
Indexed BySCI
Language英语
Funding OrganizationNational Basic Research Program of China(2012CB316300) ; National Natural Science Foundation of China(61403390 ; U1435221)
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS IDWOS:000388864400012
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12310
Collection智能感知与计算研究中心
Corresponding AuthorWu, Shu
Affiliation1.Chinese Acad Sci, Inst Automat, Ctr Res Intelligent Percept & Comp, Natl Lab Pattern Recognit, Beijing 100864, Peoples R China
2.Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China
3.IBM Res China, Beijing 100193, Peoples R China
Recommended Citation
GB/T 7714
Wu, Shu,Guo, Weiyu,Xu, Song,et al. Coupled Topic Model for Collaborative Filtering With User-Generated Content[J]. IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS,2016,46(6):908-920.
APA Wu, Shu,Guo, Weiyu,Xu, Song,Huang, Yongzhen,Wang, Liang,&Tan, Tieniu.(2016).Coupled Topic Model for Collaborative Filtering With User-Generated Content.IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS,46(6),908-920.
MLA Wu, Shu,et al."Coupled Topic Model for Collaborative Filtering With User-Generated Content".IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS 46.6(2016):908-920.
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