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Volumn , Issue , 2012, Pages 462-465

Movie swarm: Information mining technique for movie recommendation system

Author keywords

Interesting movies; movie data; movie swarm; recommendation

Indexed keywords

COLLABORATIVE FILTERING RECOMMENDATIONS; EXPERIMENTAL STUDIES; INFORMATION MINING; INTERESTING MOVIES; MOVIE DATA; MOVIE SWARM; RECOMMENDATION; TRADITIONAL SYSTEMS;

EID: 84875526594     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICECE.2012.6471587     Document Type: Conference Paper
Times cited : (7)

References (14)
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  • 4
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  • 7
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    • A personalized television listings service
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    • Smyth, B.1    Cotter, P.2
  • 9
    • 0031103679 scopus 로고    scopus 로고
    • Fab: Content-based, collaborative recommendation
    • ACM
    • M. Balabanović and Y. Shoham, "Fab: content-based, collaborative recommendation, "Communications of the ACM, vol. 40, no. 3, pp. 66-72, 1997.
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    • Balabanović, M.1    Shoham, Y.2
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    • Learning and revising user profiles: The identification of interesting web sites
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    • Pazzani, M.1    Billsus, D.2
  • 12
    • 37249036549 scopus 로고    scopus 로고
    • A hybrid approach for movie recommendation
    • G. Lekakos and P. Caravelas, "A hybrid approach for movie recommendation, "Multimedia tools and applications, vol. 36, no. 1, pp. 55-70, 2008.
    • (2008) Multimedia Tools and Applications , vol.36 , Issue.1 , pp. 55-70
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  • 13
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    • Swarm: Mining relaxed temporal moving object clusters
    • Z. Li, B. Ding, J. Han, and R. Kays, "Swarm: Mining relaxed temporal moving object clusters, "Proceedings of the VLDB Endowment, vol. 3, no. 1-2, pp. 723-734, 2010.
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    • Li, Z.1    Ding, B.2    Han, J.3    Kays, R.4
  • 14
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    • G. Research
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    • Movielens Data Sets


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.