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Volumn , Issue , 2007, Pages 863-870

On the effectiveness of prioritized user-profile and detecting active users in collaborative filtering recommender systems

Author keywords

[No Author keywords available]

Indexed keywords

ACTIVE USERS; COLLABORATIVE FILTERING; COLLABORATIVE FILTERING METHODS; DATA ENGINEERING; DATA-SETS; INTERNATIONAL CONFERENCES; PERSONALIZED RECOMMENDATION; RECOMMENDER SYSTEMS;

EID: 48349108200     PISSN: 10844627     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICDEW.2007.4401077     Document Type: Conference Paper
Times cited : (4)

References (11)
  • 4
    • 0003654042 scopus 로고    scopus 로고
    • Empirical Analysis of Predictive Algorithms for Collaborative Filtering
    • Microsoft Research, October
    • Breese, Heckermen, and Kadie, "Empirical Analysis of Predictive Algorithms for Collaborative Filtering", technical report, Microsoft Research, October 1998.
    • (1998) technical report
    • Breese, H.1    Kadie2
  • 6
    • 33646261139 scopus 로고    scopus 로고
    • Improving the prediction accuracy of recommendation algorithms: Approaches anchored on human factors
    • journal of Interacting with Computers, 18
    • G. Lekakos, G. M. Giaglis, "Improving the prediction accuracy of recommendation algorithms: Approaches anchored on human factors", journal of Interacting with Computers, 18 (2006), pp. 410-431.
    • (2006) , pp. 410-431
    • Lekakos, G.1    Giaglis, G.M.2
  • 7
    • 0033325071 scopus 로고    scopus 로고
    • A framework for collaborative, content-based and demographic filtering
    • M. Pazzani, "A framework for collaborative, content-based and demographic filtering", Artificial Intelligence Review 13 (5-6), pp. 393-408.
    • Artificial Intelligence Review , vol.13 , Issue.5-6 , pp. 393-408
    • Pazzani, M.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.