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Volumn 22, Issue 2, 2009, Pages 97-107

Applying probabilistic latent semantic analysis to multi-criteria recommender system

Author keywords

Collaborative filtering; Latent semantic analysis; Linear Gaussian regression; Multi criteria

Indexed keywords

COLLABORATIVE FILTERING; DATA SETS; GAUSSIAN MODEL; GAUSSIAN REGRESSION; LATENT SEMANTIC ANALYSIS; LINEAR GAUSSIAN REGRESSION; MACHINE LEARNING METHODS; MULTI-CRITERIA; PERFORMANCE GAIN; PROBABILISTIC LATENT SEMANTIC ANALYSIS; RECOMMENDER SYSTEMS; UNDERLYING DISTRIBUTION;

EID: 68149103275     PISSN: 09217126     EISSN: None     Source Type: Journal    
DOI: 10.3233/AIC-2009-0446     Document Type: Article
Times cited : (32)

References (16)
  • 1
    • 34250016241 scopus 로고    scopus 로고
    • New recommendation techniques for multicriteria rating systems
    • G. Adomavicius and Y.O. Kwon, New recommendation techniques for multicriteria rating systems, IEEE Intelligent Systems 22(3) (2007), 48-55.
    • (2007) IEEE Intelligent Systems , vol.22 , Issue.3 , pp. 48-55
    • Adomavicius, G.1    Kwon, Y.O.2
  • 2
    • 20844435854 scopus 로고    scopus 로고
    • Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions
    • G. Adomavicius and A. Tuzhilin, Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions, IEEE Trans. Knowl. Data Eng. 17(6) (2005), 734-749.
    • (2005) IEEE Trans. Knowl. Data Eng , vol.17 , Issue.6 , pp. 734-749
    • Adomavicius, G.1    Tuzhilin, A.2
  • 3
    • 68149127768 scopus 로고    scopus 로고
    • J.S. Breese, D. Heckerman and C.M. Kadie, Empirical analysis of predictive algorithms for collaborative filtering, in: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, University of Wisconsin Business School, Madison, WI, USA, Morgan Kaufmann, 1998, pp. 43-52.
    • J.S. Breese, D. Heckerman and C.M. Kadie, Empirical analysis of predictive algorithms for collaborative filtering, in: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, University of Wisconsin Business School, Madison, WI, USA, Morgan Kaufmann, 1998, pp. 43-52.
  • 4
    • 0034818212 scopus 로고    scopus 로고
    • Unsupervised learning by probabilistic latent semantic analysis
    • T. Hofmann, Unsupervised learning by probabilistic latent semantic analysis, Machine Learning 42(1/2) (2001), 177-196.
    • (2001) Machine Learning , vol.42 , Issue.1-2 , pp. 177-196
    • Hofmann, T.1
  • 5
    • 3042742744 scopus 로고    scopus 로고
    • Latent semantic models for collaborative filtering
    • T. Hofmann, Latent semantic models for collaborative filtering, ACM Trans. Inf. Syst. 22(1) (2004), 89-115.
    • (2004) ACM Trans. Inf. Syst , vol.22 , Issue.1 , pp. 89-115
    • Hofmann, T.1
  • 8
    • 0037252945 scopus 로고    scopus 로고
    • Amazon.com recommendations: Item-to-item collaborative filtering
    • G. Linden, B. Smith and J. York, Amazon.com recommendations: Item-to-item collaborative filtering, IEEE Internet Computing 7(1) (2003), 76-80.
    • (2003) IEEE Internet Computing , vol.7 , Issue.1 , pp. 76-80
    • Linden, G.1    Smith, B.2    York, J.3
  • 9
    • 57649179346 scopus 로고    scopus 로고
    • Designing a web-based testing tool for multi-criteria recommender systems
    • N. Manouselis and C. Costopoulou, Designing a web-based testing tool for multi-criteria recommender systems, Engineering Letters 13(3) (2006), 22.
    • (2006) Engineering Letters , vol.13 , Issue.3 , pp. 22
    • Manouselis, N.1    Costopoulou, C.2
  • 10
    • 35148812647 scopus 로고    scopus 로고
    • Analysis and classification of multi-criteria recommender systems
    • N. Manouselis and C. Costopoulou, Analysis and classification of multi-criteria recommender systems, World Wide Web 10(4)(2007), 415-441.
    • (2007) World Wide Web , vol.10 , Issue.4 , pp. 415-441
    • Manouselis, N.1    Costopoulou, C.2
  • 12
    • 80051716024 scopus 로고    scopus 로고
    • Preliminary study of the expected performance of MAUT collaborative filtering algorithms
    • Athens, Greece, Springer
    • N. Manouselis and C. Costopoulou, Preliminary study of the expected performance of MAUT collaborative filtering algorithms, in: Proceedings of WSKS'08: First World Summit on the Knowledge Society, Athens, Greece, Springer, 2008, pp. 527-536.
    • (2008) Proceedings of WSKS'08: First World Summit on the Knowledge Society , pp. 527-536
    • Manouselis, N.1    Costopoulou, C.2
  • 13
    • 31844451557 scopus 로고    scopus 로고
    • Fast maximum margin matrix factorization for collaborative prediction
    • Proceedings of the Twenty-Second International Conference, Bonn, Germany
    • J.D.M. Rennie and N. Srebro, Fast maximum margin matrix factorization for collaborative prediction, in: Proceedings of the Twenty-Second International Conference, Bonn, Germany, ACM International Conference Proceeding Series, 2005, pp. 713-719.
    • (2005) ACM International Conference Proceeding Series , pp. 713-719
    • Rennie, J.D.M.1    Srebro, N.2
  • 15
    • 1942516799 scopus 로고    scopus 로고
    • Flexible mixture model for collaborative filtering
    • Washington, DC, USA, AAAI Press
    • L. Si and R. Jin, Flexible mixture model for collaborative filtering, in: Proceedings of the Twentieth International Conference, Washington, DC, USA, AAAI Press, 2003, pp. 704-711.
    • (2003) Proceedings of the Twentieth International Conference , pp. 704-711
    • Si, L.1    Jin, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.