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Volumn 14, Issue 9, 2003, Pages 1621-1628

Collaborative filtering recommendation algorithm based on item rating prediction

Author keywords

Collaborative filtering; E commerce; Item similarity; MAE (mean absolute error); Recommendation algorithm; Recommendation system

Indexed keywords

ALGORITHMS; CUSTOMER SATISFACTION; ERROR ANALYSIS;

EID: 0348143544     PISSN: 10009825     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (210)

References (13)
  • 2
    • 84976668719 scopus 로고
    • Using collaborative filtering to weave an information tapestry
    • Goldberg D, Nichols D, Oki BM, Terry D. Using collaborative filtering to weave an information tapestry. Communications of the ACM, 1992, 35(12): 61-70.
    • (1992) Communications of the ACM , vol.35 , Issue.12 , pp. 61-70
    • Goldberg, D.1    Nichols, D.2    Oki, B.M.3    Terry, D.4
  • 7
    • 0031272327 scopus 로고    scopus 로고
    • Efficient approximations for the marginal likelihood of Bayesian networks with hidden variables
    • Chickering D, Hecherman D. Efficient approximations for the marginal likelihood of Bayesian networks with hidden variables. Machine Learning, 1997, 29(2/3): 181-212.
    • (1997) Machine Learning , vol.29 , Issue.2-3 , pp. 181-212
    • Chickering, D.1    Hecherman, D.2
  • 9
    • 0347805755 scopus 로고    scopus 로고
    • Learning mixture of DAG models
    • Technical Report, MSR-TR-97-30, Redmond: Microsoft Research
    • Thiesson B, Meek C, Chickering D, Heckerman D, Learning mixture of DAG models. Technical Report, MSR-TR-97-30, Redmond: Microsoft Research, 1997.
    • (1997)
    • Thiesson, B.1    Meek, C.2    Chickering, D.3    Heckerman, D.4
  • 13
    • 0037605074 scopus 로고    scopus 로고
    • On the effects of dimensionality reduction on high dimensional similarity search
    • Aggarwal CC. On the effects of dimensionality reduction on high dimensional similarity search. In: ACM PODS Conference. 2001.
    • (2001) ACM PODS Conference
    • Aggarwal, C.C.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.