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Domain-Sensitive Recommendation with User-Item Subgroup Analysis
Liu, Jing1; Jiang, Yu1; Li, Zechao2; Zhang, Xi1; Lu, Hanqing1
AbstractCollaborative Filtering (CF) is one of the most successful recommendation approaches to cope with information overload in the real world. However, typical CF methods equally treat every user and item, and cannot distinguish the variation of user's interests across different domains. This violates the reality that user's interests always center on some specific domains, and the users having similar tastes on one domain may have totally different tastes on another domain. Motivated by the observation, in this paper, we propose a novel Domain-sensitive Recommendation (DsRec) algorithm, to make the rating prediction by exploring the user-item subgroup analysis simultaneously, in which a user-item subgroup is deemed as a domain consisting of a subset of items with similar attributes and a subset of users who have interests in these items. The proposed framework of DsRec includes three components: a matrix factorization model for the observed rating reconstruction, a bi-clustering model for the user-item subgroup analysis, and two regularization terms to connect the above two components into a unified formulation. Extensive experiments on Movielens-100K and two real-world product review datasets show that our method achieves the better performance in terms of prediction accuracy criterion over the state-of-the-art methods.
KeywordRecommender System Matrix Factorization User-item Subgroup Collaborative Filtering
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
Funding Organization973 Program(2012CB316304) ; National Natural Science Foundation of China(61332016 ; 61272329 ; 61472422)
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Information Systems ; Engineering, Electrical & Electronic
WOS IDWOS:000372543500008
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Cited Times:8[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
2.Nanjing Univ Sci & Technol, Sch Comp Sci & Technol, Nanjing 210094, Jiangsu, Peoples R China
Recommended Citation
GB/T 7714
Liu, Jing,Jiang, Yu,Li, Zechao,et al. Domain-Sensitive Recommendation with User-Item Subgroup Analysis[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2016,28(4):939-950.
APA Liu, Jing,Jiang, Yu,Li, Zechao,Zhang, Xi,&Lu, Hanqing.(2016).Domain-Sensitive Recommendation with User-Item Subgroup Analysis.IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,28(4),939-950.
MLA Liu, Jing,et al."Domain-Sensitive Recommendation with User-Item Subgroup Analysis".IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 28.4(2016):939-950.
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