메뉴 건너뛰기




Volumn , Issue , 2013, Pages 1-6

Big & personal: Data and models behind Netflix recommendations

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; LEARNING SYSTEMS;

EID: 84890614611     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2501221.2501222     Document Type: Conference Paper
Times cited : (58)

References (20)
  • 1
    • 84889593981 scopus 로고    scopus 로고
    • Mining large streams of user data for personalized recommendations
    • X. Amatriain. Mining large streams of user data for personalized recommendations. ACM SIGKDD Explorations Newsletter, 14(2):37{48, 2013.
    • (2013) ACM SIGKDD Explorations Newsletter , vol.14 , Issue.2 , pp. 37-48
    • Amatriain, X.1
  • 2
    • 84890656495 scopus 로고    scopus 로고
    • System architectures for personalization and recommendation
    • March
    • X. Amatriain and J. Basilico. System architectures for personalization and recommendation. In the Netix Techblog: http://techblog.netix.com/2013/03/ system-architectures-for.html, March 2013.
    • (2013) The Netix Techblog
    • Amatriain, X.1    Basilico, J.2
  • 3
    • 70349798309 scopus 로고    scopus 로고
    • I like it... I like it not: Evaluating user ratings noise in recommender systems
    • chapter 24, Springer Berlin
    • X. Amatriain, J. M. Pujol, and N. Oliver. I Like It... I Like It Not: Evaluating User Ratings Noise in Recommender Systems. In User Modeling, Adaptation, and Personalization, volume 5535, chapter 24, pages 247{258. Springer Berlin, 2009.
    • (2009) User Modeling, Adaptation, and Personalization , vol.5535 , pp. 247-258
    • Amatriain, X.1    Pujol, J.M.2    Oliver, N.3
  • 4
    • 57349146373 scopus 로고    scopus 로고
    • Lessons from the netix prize challenge
    • December
    • R. M. Bell and Y. Koren. Lessons from the Netix Prize Challenge. SIGKDD Explor. Newsl., 9(2):75{79, December 2007.
    • (2007) SIGKDD Explor. Newsl. , vol.9 , Issue.2 , pp. 75-79
    • Bell, R.M.1    Koren, Y.2
  • 5
    • 77953642308 scopus 로고    scopus 로고
    • Efficient algorithms for ranking with svms
    • June
    • O. Chapelle and S. S. Keerthi. Efficient algorithms for ranking with SVMs. Information Retrieval, 13:201{215, June 2010.
    • (2010) Information Retrieval , vol.13 , pp. 201-215
    • Chapelle, O.1    Keerthi, S.S.2
  • 6
    • 4644367942 scopus 로고    scopus 로고
    • An efficient boosting algorithm for combining preferences
    • December
    • Y. Freund, R. Iyer, R. E. Schapire, and Y. Singer. An efficient boosting algorithm for combining preferences. J. Mach. Learn. Res., 4:933{969, December 2003.
    • (2003) J. Mach. Learn. Res. , vol.4 , pp. 933-969
    • Freund, Y.1    Iyer, R.2    Schapire, R.E.3    Singer, Y.4
  • 9
    • 84455207062 scopus 로고    scopus 로고
    • A stochastic learning-to-rank algorithm and its application to contextual advertising
    • M. Karimzadehgan, W. Li, R. Zhang, and J. Mao. A stochastic learning-to-rank algorithm and its application to contextual advertising. In Proceedings of the 20th WWW, 2011.
    • (2011) Proceedings of the 20th WWW
    • Karimzadehgan, M.1    Li, W.2    Zhang, R.3    Mao, J.4
  • 10
    • 65449121157 scopus 로고    scopus 로고
    • Factorization meets the neighborhood: A multifaceted collaborative filtering model
    • Y. Koren. Factorization meets the neighborhood: A multifaceted collaborative filtering model. In Proceedings of the 14th ACM SIGKDD, 2008.
    • (2008) Proceedings of the 14th ACM SIGKDD
    • Koren, Y.1
  • 12
    • 85008044987 scopus 로고    scopus 로고
    • Matrix factorization techniques for recommender systems
    • August
    • Y. Koren, R. Bell, and C. Volinsky. Matrix Factorization Techniques for Recommender Systems. Computer, 42(8):30{37, August 2009.
    • (2009) Computer , vol.42 , Issue.8 , pp. 30-37
    • Koren, Y.1    Bell, R.2    Volinsky, C.3
  • 14
    • 84873533505 scopus 로고    scopus 로고
    • Dynamic playlist generation based on skipping behavior
    • E. Pampalk, T. Pohle, and G. Widmer. Dynamic playlist generation based on skipping behavior. In ISMIR, volume 5, pages 634{637, 2005.
    • (2005) ISMIR , vol.5 , pp. 634-637
    • Pampalk, E.1    Pohle, T.2    Widmer, G.3
  • 18
    • 79960495877 scopus 로고    scopus 로고
    • Designing and evaluating explanations for recommender systems
    • Springer
    • N. Tintarev and J. Masthoff. Designing and evaluating explanations for recommender systems. In Recommender Systems Handbook, pages 479{510. Springer, 2011.
    • (2011) Recommender Systems Handbook , pp. 479-510
    • Tintarev, N.1    Masthoff, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.