Employing rough set theory to alleviate the sparsity issue in recommender system

Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC

Volumn 3, Issue , 2008, Pages 1610-1614

  Huang, Chong Ben ^a   Gong, Song Jie ^a  

^a ZHEJIANG BUSINESS TECHNOLOGY INSTITUTE   (China)

Author keywords

Collaborative filtering; Recommender system; Rough set theory; Sparsity

Indexed keywords

CONTROL THEORY; CYBERNETICS; FUZZY SETS; INFORMATION RETRIEVAL SYSTEMS; LEARNING SYSTEMS; ROBOT LEARNING; SET THEORY; SIGNAL FILTERING AND PREDICTION; SINGULAR VALUE DECOMPOSITION;

APPLICATION DOMAINS; COLLABORATIVE FILTERING; INFORMATION ITEMS; PERSONALIZED SERVICES; PREDICTED VALUES; RECOMMENDATION QUALITIES; RECOMMENDER SYSTEM; SINGULAR VALUE DECOMPOSITION TECHNIQUES; SPARSITY; USER'S INTERESTS;

ROUGH SET THEORY;

EID: 57749101464     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLC.2008.4620663     Document Type: Conference Paper

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