Addressing cold start in recommender systems: A semi-supervised co-training algorithm

SIGIR 2014 - Proceedings of the 37th International ACM SIGIR Conference on Research and Development in Information Retrieval

Volumn , Issue , 2014, Pages 73-82

  Zhang, Mi ^a,b   Tang, Jie ^c   Zhang, Xuchen ^a,b   Xue, Xiangyang ^a,b  

^a FUDAN UNIVERSITY   (China)

^b Shanghai Key Laboratory of Intelligent Information Processing   (China)

^c TSINGHUA UNIVERSITY   (China)

Author keywords

Cold start; Recommendation; Semi supervised learning

Indexed keywords

LEARNING ALGORITHMS; MATHEMATICAL MODELS; RECOMMENDER SYSTEMS;

CO-TRAINING ALGORITHM; COLD-START; ENSEMBLE LEARNING ALGORITHM; RECOMMENDATION; RECOMMENDATION ACCURACY; RECOMMENDATION METHODS; RECOMMENDATION PERFORMANCE; SEMI-SUPERVISED LEARNING;

SUPERVISED LEARNING;

EID: 84904556934     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2600428.2609599     Document Type: Conference Paper

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