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Volumn , Issue , 2013, Pages 643-653

HETEROMF: Recommendation in heterogeneous information networks using context dependent factor models

Author keywords

Cold start; Matrix factorization; Multi context; Recommendation

Indexed keywords

AMOUNT OF INFORMATION; COLD START; COLLECTIVE MATRIX FACTORIZATIONS; HETEROGENEOUS INFORMATION; MATRIX FACTORIZATIONS; MULTI-CONTEXT; REAL LIFE DATASETS; RECOMMENDATION;

EID: 84893033731     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (86)

References (24)
  • 1
    • 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 Transactions on Knowledge and Data Engineering, 17(6):734-749, 2005.
    • (2005) IEEE Transactions on Knowledge and Data Engineering , vol.17 , Issue.6 , pp. 734-749
    • Adomavicius, G.1    Tuzhilin, A.2
  • 8
    • 85008044987 scopus 로고    scopus 로고
    • Matrix factorization techniques for recommender systems
    • Y. Koren, R. Bell, and C. Volinsky. Matrix factorization techniques for recommender systems. IEEE Computer, 42:30-37, 2009.
    • (2009) IEEE Computer , vol.42 , pp. 30-37
    • Koren, Y.1    Bell, R.2    Volinsky, C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.