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Volumn , Issue , 2010, Pages 249-252

Do clicks measure recommendation relevancy? An empirical user study

Author keywords

Click through rate; Collaborative filtering; Evaluation; Relevance

Indexed keywords

CLICK-THROUGH RATE; COLLABORATIVE FILTERING; EVALUATION; ON-LINE EVALUATION; ON-LINE TESTS; ONLINE DATA; REAL APPLICATIONS; RECOMMENDATION SYSTEMS; RECOMMENDER SYSTEMS; RELEVANCE; USER STUDY;

EID: 78649927237     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1864708.1864759     Document Type: Conference Paper
Times cited : (35)

References (12)
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    • (2003) CHI ' 03 , pp. 585-592
    • Cosley, D.1    Lam, S.K.2    Albert, I.3    Konstan, J.A.4    Riedl, J.5
  • 4
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    • Item-based top-n recommendation algorithms
    • M. Deshpande and G. Karypis. Item-based top-n recommendation algorithms. ACM Trans. Inf. Syst., 22(1):143-177, 2004.
    • (2004) ACM Trans. Inf. Syst. , vol.22 , Issue.1 , pp. 143-177
    • Deshpande, M.1    Karypis, G.2
  • 7
    • 0037252945 scopus 로고    scopus 로고
    • Amazon.com recommendations: Item-to-item collaborative filtering
    • G. Linden, B. Smith, and J. York. Amazon.com recommendations: Item-to-item collaborative filtering. IEEE Internet Computing, 7(1):76-80, 2003.
    • (2003) IEEE Internet Computing , vol.7 , Issue.1 , pp. 76-80
    • Linden, G.1    Smith, B.2    York, J.3
  • 8
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    • Personalized news recommendation based on click behavior
    • J. Liu, P. Dolan, and E. R. Pedersen. Personalized news recommendation based on click behavior. In IUI, pages 31-40, 2010.
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  • 9
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    • Being accurate is not enough: How accuracy metrics have hurt recommender systems
    • Montreal, Canada, April
    • S. McNee, J. Riedl, and J. Konstan. Being Accurate is Not Enough: How Accuracy Metrics Have Hurt Recommender Systems. In Extended Abstracts CHI'06,Montreal, Canada, April 2006.
    • (2006) Extended Abstracts CHI'06
    • McNee, S.1    Riedl, J.2    Konstan, J.3
  • 10
    • 38349029576 scopus 로고    scopus 로고
    • Content-based recommendation systems
    • M. Pazzani and D. Billsus. Content-Based Recommendation Systems. The Adaptive Web, 4321:325-341, 2007.
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    • Pazzani, M.1    Billsus, D.2
  • 11
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    • Cofi rank - Maximum margin matrix factorization for collaborative ranking
    • M. Weimer, A. Karatzoglou, Q. V. Le, and A. J. Smola. Cofi rank - maximum margin matrix factorization for collaborative ranking. In NIPS, 2007.
    • (2007) NIPS
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.