메뉴 건너뛰기




Volumn 2, Issue 3, 2011, Pages

Learning to recommend with explicit and implicit social relations

Author keywords

Matrix factorization; Recommender systems; Social network; Social trust ensemble

Indexed keywords

COMPLEXITY ANALYSIS; LARGE DATASETS; MATRIX; MATRIX FACTORIZATIONS; PROBABILISTIC FACTORS; REAL-WORLD; SOCIAL NETWORK; SOCIAL RELATIONS; SOCIAL TRUST ENSEMBLE; STATE-OF-THE-ART APPROACH;

EID: 79955688653     PISSN: 21576904     EISSN: 21576912     Source Type: Journal    
DOI: 10.1145/1961189.1961201     Document Type: Article
Times cited : (145)

References (35)
  • 3
    • 36849079891 scopus 로고    scopus 로고
    • Modeling relationships at multiple scales to improve accuracy of large recommender systems
    • DOI 10.1145/1281192.1281206, KDD-2007: Proceedings of the Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
    • Bell, R., Koren, Y., and VoLiNSKY, C. 2007. Modeling relationships at multiple scales to improve accuracy of large recommender systems. In Proceedings of the International SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'07). 95-104. (Pubitemid 350229196)
    • (2007) Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , pp. 95-104
    • Bell, R.1    Koren, Y.2    Volinsky, C.3
  • 5
    • 0036993076 scopus 로고    scopus 로고
    • Collaborative filtering with privacy via factor analysis. in
    • ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'02)
    • Canny, J. 2002. Collaborative filtering with privacy via factor analysis. In Proceedings of the Annual ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'02). 238-245.
    • (2002) Proceedings of the Annual , pp. 238-245
    • Canny, J.1
  • 6
    • 3042821101 scopus 로고    scopus 로고
    • Item-Based top-n recommendation
    • Deshpande, M. and KARYPis, G. 2004. Item-Based top-n recommendation. ACM Trans. Inf. Syst. 22, 1, 143-177.
    • (2004) ACM Trans. Inf. Syst. , vol.22 , Issue.1 , pp. 143-177
    • Deshpande, M.1    Karypis, G.2
  • 9
    • 3042742744 scopus 로고    scopus 로고
    • Latent semantic models for collaborative filtering
    • Hofmann, T. 2004. Latent semantic models for collaborative filtering. ACM Trans. Inf. Syst. 22, 1, 89-115.
    • (2004) ACM Trans. Inf. Syst. , vol.22 , Issue.1 , pp. 89-115
    • Hofmann, T.1
  • 14
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
    • LEE, D.D.and Seung, H. S. 1999. Learning the parts of objects by non-negative matrix factorization. Nature 401, 6755, 788-791.
    • (1999) Nature , vol.401 , Issue.6755 , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 15
    • 0037252945 scopus 로고    scopus 로고
    • Amazon. com recommendations: Item-to-Item collaborative filtering
    • Linden, G., Smith, B., and YoRK, J. 2003. Amazon.com recommendations: Item-to-Item collaborative filtering. IEEE Internet Comput. 7, 1, 76-80.
    • (2003) IEEE Internet Comput. , vol.7 , Issue.1 , pp. 76-80
    • Linden, G.1    Smith, B.2    York, J.3
  • 30
    • 0038959172 scopus 로고    scopus 로고
    • Probabilistic principal component analysis
    • TiPPiNG, M.E. and Bishop, C. M. 1999. Probabilistic principal component analysis. J. Roy. Statist. Soc. B61, 3, 611-622.
    • (1999) J. Roy. Statist. Soc. , vol.B61 , Issue.3 , pp. 611-622
    • Tipping, M.E.1    Bishop, C.M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.