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Volumn , Issue , 2011, Pages 69-76

Distributed rating prediction in user generated content streams

Author keywords

distributed system; recommendation system

Indexed keywords

ACCURATE PREDICTION; CONVERGENCE PROPERTIES; DATA SETS; DISTRIBUTED SYSTEMS; FACEBOOK; FAST CONVERGENCE; GRADIENT DESCENT ALGORITHMS; MATRIX FACTORIZATIONS; NEWSFEEDS; ONLINE EXPERIMENT; PREDICTION PROBLEM; RECOMMENDATION SYSTEM; ROOT MEAN SQUARE ERRORS; THIRD PARTIES; USER RATING; USER-GENERATED CONTENT;

EID: 82555204536     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2043932.2043948     Document Type: Conference Paper
Times cited : (26)

References (25)
  • 2
    • 82555195673 scopus 로고    scopus 로고
    • US seeks web privacy 'bill of rights'
    • Dec. 17th
    • ANGWIN, J. US seeks web privacy 'bill of rights'. Wall Street Journal (Dec. 17th 2010).
    • (2010) Wall Street Journal
    • Angwin, J.1
  • 3
    • 49749086487 scopus 로고    scopus 로고
    • Scalable collaborative filtering with jointly derived neighborhood interpolation weights
    • BELL, R. M., AND KOREN, Y. Scalable collaborative filtering with jointly derived neighborhood interpolation weights. In Proc. IEEE ICDM (2007).
    • Proc. IEEE ICDM (2007)
    • Bell, R.M.1    Koren, Y.2
  • 4
    • 82555183852 scopus 로고    scopus 로고
    • Privacy concerns and information disclosure: An illusion of control hypothesis
    • BRANDIMARTE, L., ACQUISTI, A., AND LOEWENSTEIN, G. Privacy concerns and information disclosure: An illusion of control hypothesis. In Proc. CIST (2010).
    • Proc. CIST (2010)
    • Brandimarte, L.1    Acquisti, A.2    Loewenstein, G.3
  • 5
    • 77951528523 scopus 로고    scopus 로고
    • The power of convex relaxation: Near-optimal matrix completion
    • CANDÈS, E., AND TAO, T. The power of convex relaxation: Near-optimal matrix completion. IEEE Trans. Inform. Theory 56, 5 (2009), 2053-2080.
    • (2009) IEEE Trans. Inform. Theory , vol.56 , Issue.5 , pp. 2053-2080
    • Candès, E.1    Tao, T.2
  • 6
    • 71049116435 scopus 로고    scopus 로고
    • Exact matrix completion via convex optimization
    • CANDÈS, E. J., AND RECHT, B. Exact matrix completion via convex optimization. Found. of Comput. Math. 9 (2008), 717-772.
    • (2008) Found. of Comput. Math. , vol.9 , pp. 717-772
    • Candès, E.J.1    Recht, B.2
  • 7
    • 0036993076 scopus 로고    scopus 로고
    • Collaborative filtering with privacy via factor analysis
    • CANNY, J. Collaborative filtering with privacy via factor analysis. In Proc. ACM SIGIR (2002).
    • Proc. ACM SIGIR (2002)
    • Canny, J.1
  • 8
    • 82555195669 scopus 로고    scopus 로고
    • Personalized Communities in a Distributed Recommender System
    • CASTAGNOS, S., AND BOYER, A. Personalized Communities in a Distributed Recommender System. In Proc. ECIR (2007).
    • Proc. ECIR (2007)
    • Castagnos, S.1    Boyer, A.2
  • 11
    • 77956909553 scopus 로고    scopus 로고
    • Matrix completion from noisy entries
    • KESHAVAN, R., MONTANARI, A., AND OH, S. Matrix completion from noisy entries. JMLR 11 (2010), 2057-2078.
    • (2010) JMLR , vol.11 , pp. 2057-2078
    • Keshavan, R.1    Montanari, A.2    Oh, S.3
  • 13
    • 77950364314 scopus 로고    scopus 로고
    • Collaborative filtering with temporal dynamics
    • KOREN, Y. Collaborative filtering with temporal dynamics. In Proc. ACM KDD (2009).
    • Proc. ACM KDD (2009)
    • Koren, Y.1
  • 14
    • 42149132726 scopus 로고    scopus 로고
    • Private distributed collaborative filtering using estimated concordance measures
    • LATHIA, N., HAILES, S., AND CAPRA, L. Private distributed collaborative filtering using estimated concordance measures. In Proc. ACM RecSys (Oct. 2007).
    • Proc. ACM RecSys (Oct. 2007)
    • Lathia, N.1    Hailes, S.2    Capra, L.3
  • 19
    • 46749122242 scopus 로고    scopus 로고
    • Privacy-preserving collaborative filtering using randomized perturbation techniques
    • POLAT, H., AND DU, W. Privacy-preserving collaborative filtering using randomized perturbation techniques. In Proc. IEEE ICDM (2003).
    • Proc. IEEE ICDM (2003)
    • Polat, H.1    Du, W.2
  • 20
    • 62149116834 scopus 로고    scopus 로고
    • A peer-to-peer recommender system based on spontaneous affinities
    • RUFFO, G., AND SCHIFANELLA, R. A peer-to-peer recommender system based on spontaneous affinities. ACM Transactions on Internet Technology 9 (2009), 1-34.
    • (2009) ACM Transactions on Internet Technology , vol.9 , pp. 1-34
    • Ruffo, G.1    Schifanella, R.2
  • 22
    • 64149121935 scopus 로고    scopus 로고
    • Scalable collaborative filtering approaches for large recommender systems
    • TAKÁCS, G., PILÁSZY, I., NÉMETH, B., AND TIKK, D. Scalable collaborative filtering approaches for large recommender systems. JMLR 10 (2009), 623-656.
    • (2009) JMLR , vol.10 , pp. 623-656
    • Takács, G.1    Pilászy, I.2    Németh, B.3    Tikk, D.4
  • 23
    • 82555187556 scopus 로고    scopus 로고
    • Google agonizes on privacy as ad world vaults ahead
    • Aug. 10th
    • VASCELLARO, J. E. Google agonizes on privacy as ad world vaults ahead. Wall Street Journal (Aug. 10th 2010).
    • (2010) Wall Street Journal
    • Vascellaro, J.E.1
  • 25
    • 78650205494 scopus 로고    scopus 로고
    • Microsoft quashed effort to boost online privacy
    • Aug. 2nd
    • WINGFIELD, N. Microsoft quashed effort to boost online privacy. Wall Street Journal (Aug. 2nd 2010).
    • (2010) Wall Street Journal
    • Wingfield, N.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.