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Volumn 72, Issue 3, 2008, Pages 231-245

A collaborative filtering framework based on both local user similarity and global user similarity

Author keywords

Collaborative filtering; Information theory; Similarity measure

Indexed keywords

GRAPH THEORY; INFORMATION SERVICES; SEARCH ENGINES; TOPOLOGY; VECTORS;

EID: 48349093367     PISSN: 08856125     EISSN: 15730565     Source Type: Journal    
DOI: 10.1007/s10994-008-5068-4     Document Type: Conference Paper
Times cited : (85)

References (23)
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    • Fouss, F., Pirotte, A., Renders, J. M., & Saerens, M. (2007). Random-walk computation of similarities between nodes of a graph with application to collaborative recommendation. IEEE Transactions on Knowledge and Data Engineering, 355-369.
    • (2007) IEEE Transactions on Knowledge and Data Engineering , pp. 355-369
    • Fouss, F.1    Pirotte, A.2    Renders, J.M.3    Saerens, M.4
  • 6
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    • ItemRank: A random-walk based scoring algorithm for recommender engines
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    • Gori, M.1    Pucci, A.2
  • 12
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    • Amazon.com recommendations: Item-to-item collaborative filtering
    • 1
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    • (2003) IEEE Transactions on Internet Computing , vol.7 , pp. 76-80
    • Linden, G.1    Smith, B.2    York, J.3
  • 14
    • 84898970398 scopus 로고    scopus 로고
    • Modeling user rating profiles for collaborative filtering
    • Marlin, B. (2004a). Modeling user rating profiles for collaborative filtering. Advances in Neural Information Processing Systems, 16, 627-634.
    • (2004) Advances in Neural Information Processing Systems , vol.16 , pp. 627-634
    • Marlin, B.1
  • 16
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    • The double exponential distribution: Using calculus to find a maximum likelihood estimator
    • 2
    • Norton, R. M. (1984). The double exponential distribution: Using calculus to find a maximum likelihood estimator. The American Statistician, 38(2), 135-136.
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    • Norton, R.M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.