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Volumn , Issue , 2013, Pages 443-446

Dynamic generation of personalized hybrid recommender systems

Author keywords

Hybrid recommender system; Recommender systems; Selflearning

Indexed keywords

HYBRID RECOMMENDATION; HYBRID RECOMMENDER SYSTEMS; LEARNING EFFECTIVENESS; MACHINE LEARNING TECHNIQUES; ONLINE LEARNING STRATEGY; OPTIMIZATION APPROACH; RECOMMENDATION ALGORITHMS; SELF-LEARNING;

EID: 84887589590     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2507157.2508069     Document Type: Conference Paper
Times cited : (24)

References (14)
  • 2
    • 0036959356 scopus 로고    scopus 로고
    • Hybrid recommender systems: Survey and experiments
    • Robin Burke. Hybrid recommender systems: Survey and experiments. User modeling and user-adapted interaction, 12(4):331-370, 2002.
    • (2002) User Modeling and User-adapted Interaction , vol.12 , Issue.4 , pp. 331-370
    • Burke, R.1
  • 3
    • 20844435854 scopus 로고    scopus 로고
    • Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions
    • Gediminas Adomavicius and Alexander Tuzhilin. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. Knowledge and Data Engineering, IEEE Transactions on, 17(6):734-749, 2005.
    • (2005) Knowledge and Data Engineering, IEEE Transactions on , vol.17 , Issue.6 , pp. 734-749
    • Adomavicius, G.1    Tuzhilin, A.2
  • 6
    • 84867356407 scopus 로고    scopus 로고
    • When recommenders fail: Predicting recommender failure for algorithm selection and combination
    • ACM
    • Michael Ekstrand and John Riedl. When recommenders fail: predicting recommender failure for algorithm selection and combination. In Proc. 6th ACM Conf. Recommender systems (RecSys 2012), pages 233-236. ACM, 2012.
    • (2012) Proc. 6th ACM Conf. Recommender Systems (RecSys 2012) , pp. 233-236
    • Ekstrand, M.1    Riedl, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.