Coupled Topic Model for Collaborative Filtering With User-Generated Content
文献类型:期刊论文
作者 | Wu, Shu1; Guo, Weiyu2; Xu, Song3; Huang, Yongzhen1; Wang, Liang1; Tan, Tieniu1 |
刊名 | IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS |
出版日期 | 2016-12-01 |
卷号 | 46期号:6页码:908-920 |
关键词 | Collaborative Filtering (Cf) Recommender Systems (Rs) Topic Model User-generated Content (Ugc) |
DOI | 10.1109/THMS.2016.2586480 |
文献子类 | Article |
英文摘要 | The 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. |
WOS关键词 | SYSTEMS |
WOS研究方向 | Computer Science |
语种 | 英语 |
WOS记录号 | WOS:000388864400012 |
资助机构 | National Basic Research Program of China(2012CB316300) ; National Natural Science Foundation of China(61403390 ; U1435221) |
源URL | [http://ir.ia.ac.cn/handle/173211/12310] |
专题 | 自动化研究所_智能感知与计算研究中心 |
通讯作者 | Wu, Shu |
作者单位 | 1.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 |
推荐引用方式 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. |
入库方式: OAI收割
来源:自动化研究所
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