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Contextual Operation for Recommender Systems
Wu, Shu; Liu, Qiang; Wang, Liang; Tan, Tieniu
AbstractWith the rapid growth of various applications on the Internet, recommender systems become fundamental for helping users alleviate the problem of information overload. Since contextual information is a significant factor in modeling the user behavior, various context-aware recommendation methods have been proposed recently. The state-of-the-art context modeling methods usually treat contexts as certain dimensions similar to those of users and items, and capture relevances between contexts and users/items. However, such kind of relevance has much difficulty in explanation. Some works on multi-domain relation prediction can also be used for the context-aware recommendation, but they have limitations in generating recommendations under a large amount of contextual information. Motivated by recent works in natural language processing, we represent each context value with a latent vector, and model the contextual information as a semantic operation on the user and item. Besides, we use the contextual operating tensor to capture the common semantic effects of contexts. Experimental results show that the proposed Context Operating Tensor (COT) model yields significant improvements over the competitive compared methods on three typical datasets. From the experimental results of COT, we also obtain some interesting observations which follow our intuition.
KeywordRecommender Systems Context-aware Contextual Information Context Representation Context Operation
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
Funding OrganizationNational Basic Research Program of China(2012CB316300) ; National Natural Science Foundation of China(61403390 ; U1435221)
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems ; Engineering, Electrical & Electronic
WOS IDWOS:000380122200005
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Cited Times:13[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
AffiliationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Ctr Res Intelligent Percept & Comp, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Wu, Shu,Liu, Qiang,Wang, Liang,et al. Contextual Operation for Recommender Systems[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2016,28(8):2000-2012.
APA Wu, Shu,Liu, Qiang,Wang, Liang,&Tan, Tieniu.(2016).Contextual Operation for Recommender Systems.IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,28(8),2000-2012.
MLA Wu, Shu,et al."Contextual Operation for Recommender Systems".IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 28.8(2016):2000-2012.
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