메뉴 건너뛰기




Volumn 5, Issue 1, 2014, Pages 47-64

(Partial) user preference similarity as classification-based model similarity

Author keywords

cold start problem; collaborative filtering; partial user similarity; User similarity

Indexed keywords


EID: 84918550184     PISSN: 15700844     EISSN: 22104968     Source Type: Journal    
DOI: 10.3233/SW-130099     Document Type: Conference Paper
Times cited : (6)

References (35)
  • 2
    • 0031103679 scopus 로고    scopus 로고
    • Fab: Content-based, collaborative recommendation
    • New York, NY, USA
    • M. Balabanovic and Y. Shoham, Fab: Content-based, collaborative recommendation, in: Communications of the ACM, ACM, Vol. 40, New York, NY, USA, 1997, pp. 66-72.
    • (1997) Communications of the ACM, ACM , vol.40 , pp. 66-72
    • Balabanovic, M.1    Shoham, Y.2
  • 3
    • 0031640270 scopus 로고    scopus 로고
    • Recommendation as classification: Using social and content-based information in recommendation
    • AAAI Press
    • C. Basu, H. Hirsh, and W. Cohen, Recommendation as classification: Using social and content-based information in recommendation, in: Proc. of the 15th National Conference on Artificial Intelligence, AAAI Press, 1998, pp. 714-720.
    • (1998) Proc. of the 15th National Conference on Artificial Intelligence , pp. 714-720
    • Basu, C.1    Hirsh, H.2    Cohen, W.3
  • 5
    • 45049087177 scopus 로고    scopus 로고
    • Mediation of user models for enhanced personalization in recommender systems
    • S. Berkovsky, T. Kuflik, and F. Ricci, Mediation of user models for enhanced personalization in recommender systems, in: User Modeling and User-Adapted Interaction, Vol. 18, 2007, pp. 245-286.
    • (2007) User Modeling and User-Adapted Interaction , vol.18 , pp. 245-286
    • Berkovsky, S.1    Kuflik, T.2    Ricci, F.3
  • 8
    • 0002051628 scopus 로고    scopus 로고
    • Empirical analysis of predictive algorithms for collaborative filtering
    • Morgan Kaufmann
    • J.S. Breese, D. Heckerman, and C. Kadie, Empirical analysis of predictive algorithms for collaborative filtering, in: 14th Conference on Uncertainty in AI, Morgan Kaufmann, 1998, pp. 43-52.
    • (1998) 14th Conference on Uncertainty in AI , pp. 43-52
    • Breese, J.S.1    Heckerman, D.2    Kadie, C.3
  • 9
    • 0036959356 scopus 로고    scopus 로고
    • Hybrid recommender systems: Survey and experiments
    • October
    • R. Burke, Hybrid recommender systems: Survey and experiments, User Modeling and User-Adapted Interaction 12(4), 331-370, October 2002.
    • (2002) User Modeling and User-Adapted Interaction , vol.12 , Issue.4 , pp. 331-370
    • Burke, R.1
  • 10
    • 57349141441 scopus 로고    scopus 로고
    • A multilayer ontology-based hybrid recommendation model
    • I. Cantador, A. Bellogín, and P. Castells, A multilayer ontology-based hybrid recommendation model, AI Communcations 21(2-3) (2008), 202-210.
    • (2008) AI Communcations , vol.21 , Issue.2-3 , pp. 202-210
    • Cantador, I.1    Bellogín, A.2    Castells, P.3
  • 12
    • 33749062774 scopus 로고    scopus 로고
    • Filmtrust: Movie recommendations using trust in web-based social networks
    • Las Vegas, NV, January
    • J. Golbeck and J. Hendler, Filmtrust: Movie recommendations using trust in web-based social networks, in: Proc. of the IEEE Consumer Communications and Networking Conference, Vol. 1, Las Vegas, NV, January 2006, pp. 282-286
    • (2006) Proc. of the IEEE Consumer Communications and Networking Conference , vol.1 , pp. 282-286
    • Golbeck, J.1    Hendler, J.2
  • 16
    • 0031103689 scopus 로고    scopus 로고
    • Referral web: Combining social networks and collaborative filtering
    • H. Kautz, B. Selman, and M. Shah, Referral web: Combining social networks and collaborative filtering, Communications of the ACM 40(3) (1997), 63-65.
    • (1997) Communications of the ACM , vol.40 , Issue.3 , pp. 63-65
    • Kautz, H.1    Selman, B.2    Shah, M.3
  • 17
    • 3042701774 scopus 로고    scopus 로고
    • Introduction to recommender systems: Algorithms and evaluation
    • J.A. Konstan, Introduction to recommender systems: Algorithms and evaluation, ACM Transactions on Information Systems 22(1) (2004), 1-4.
    • (2004) ACM Transactions on Information Systems , vol.22 , Issue.1 , pp. 1-4
    • Konstan, J.A.1
  • 18
    • 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, Internet Computing, IEEE 7(1) (2003), 76-80.
    • (2003) Internet Computing, IEEE , vol.7 , Issue.1 , pp. 76-80
    • Linden, G.1    Smith, B.2    York, J.3
  • 23
    • 0004255908 scopus 로고    scopus 로고
    • McGraw Hill Higher Education, October
    • T.M. Mitchel, Machine Learning, McGraw Hill Higher Education, October 1997.
    • (1997) Machine Learning
    • Mitchel, T.M.1
  • 25
    • 77953964871 scopus 로고    scopus 로고
    • Clustknn: A highly scalable hybrid model-and memory-based cg algorithm
    • August
    • A.M. Rashid, S.K. Lam, G. Karypis, and J. Riedl, Clustknn: A highly scalable hybrid model-and memory-based cg algorithm, in: WEBKDD, August 2006.
    • (2006) WEBKDD
    • Rashid, A.M.1    Lam, S.K.2    Karypis, G.3    Riedl, J.4
  • 33
    • 29844440003 scopus 로고    scopus 로고
    • Semantic web recommender systems
    • Ph.D. Workshop 2004, March
    • C.-N. Ziegler, Semantic web recommender systems, in: Proc. of the Joint ICDE/EDBT Ph.D. Workshop 2004, March 2004.
    • (2004) Proc. of the Joint ICDE/EDBT
    • Ziegler, C.-N.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.