Cross-domain collaborative recommendation in a cold-start context: The impact of user profile size on the quality of recommendation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7899 LNCS, Issue , 2013, Pages 289-295

  Sahebi, Shaghayegh ^a   Brusilovsky, Peter ^a  

^a UNIVERSITY OF PITTSBURGH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COLD START PROBLEMS; COLLABORATIVE RECOMMENDATION; CROSS-DOMAIN RECOMMENDATIONS; DIFFERENT DOMAINS; LARGE VOLUMES; QUALITY OF RECOMMENDATIONS; RESEARCH STUDIES; SINGLE DOMAINS;

MATHEMATICAL MODELS;

RECOMMENDER SYSTEMS;

EID: 84884488145     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-38844-6_25     Document Type: Conference Paper

References (6)

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2. Berkovsky, S., Kuflik, T., Ricci, F.: Mediation of user models for enhanced personalization in recommender systems. User Modeling and User-Adapted Interaction, UMUAI 2008 18(3) (August 2008)
3. Cremonesi, P., Tripodi, A., Turrin, R.: Cross-domain recommender systems. In: 2011 IEEE 11th International Conference on Data Mining Data Mining Workshops (ICDMW), pp. 496-503 (December 2011)
4. Pan, W., Xiang, E.W., Liu, N.N., Yang, Q.: Transfer learning in collaborative filtering for sparsity reduction. In: Artificial Intelligence, AAAI 2010 (2010)
5. Sahebi, S., Cohen, W.: Community-based recommendations: a solution to the cold start problem. In: RSWEB, in Conjunction with ACM RecSys 2011 (2011)
6. Schein, A.I., Popescul, A., Ungar, L.H., Pennock, D.M.: Methods and metrics for cold-start recommendations. In: Special Interest Group in Information Retrieval, SIGIR 2002, New York, NY, USA (2002)