Learning multiple-question decision trees for cold-start recommendation

WSDM 2013 - Proceedings of the 6th ACM International Conference on Web Search and Data Mining

Volumn , Issue , 2013, Pages 445-454

  Sun, Mingxuan ^a   Li, Fuxin ^a   Lee, Joonseok ^a   Zhou, Ke ^a   Lebanon, Guy ^a   Zha, Hongyuan ^a  

^a Georgia Institute of Technology   (United States)

Author keywords

cold start problem; collaborative filtering; decision tree; recommender systems

Indexed keywords

CHILD NODE; COGNITIVE EFFORTS; COLD START PROBLEMS; COLD-START RECOMMENDATIONS; CORRESPONDING WEIGHTS; INNER PRODUCT; MULTIPLE ITEMS; NOVEL ALGORITHM; OPTIMIZATION FRAMEWORK; PREDICTION ACCURACY; QUANTITATIVE EXPERIMENTAL VALIDATION; STATE-OF-THE-ART APPROACH; USER STUDY; WEIGHT VECTOR;

ALGORITHMS; COLLABORATIVE FILTERING; CONSTRAINED OPTIMIZATION; DATA MINING; DECISION TREES; INFORMATION RETRIEVAL; RECOMMENDER SYSTEMS; WEBSITES;

SURVEYS;

EID: 84874246335     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2433396.2433451     Document Type: Conference Paper

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