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Volumn , Issue , 2013, Pages 785-788

Optimizing top-N collaborative filtering via dynamic negative item sampling

Author keywords

Negative Item Sampling; Ranking Oriented Collaborative Filtering; Recommender Systems

Indexed keywords

COLLABORATIVE FILTERING TECHNIQUES; LARGE-SCALE DATASETS; LEARNING MODELS; PERFORMANCE GAIN; PREDICTION MODEL; PREFERENCE DATA; TRAINING EXAMPLE; TRAINING SAMPLE;

EID: 84883124364     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2484028.2484126     Document Type: Conference Paper
Times cited : (272)

References (10)
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  • 2
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    • Lu, Q.1    Chen, T.2    Zhang, W.3    Yang, D.4    Yu, Y.5
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    • Y. Shi, M. Larson, and A. Hanjalic. List-wise learning to rank with matrix factorization for collaborative filtering. In RecSys, 2010.
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    • Shi, Y.1    Larson, M.2    Hanjalic, A.3
  • 9
    • 48349104603 scopus 로고    scopus 로고
    • Cofirank-maximum margin matrix factorization for collaborative ranking
    • M. Weimer, A. Karatzoglou, Q. Le, A. Smola, et al Cofirank-maximum margin matrix factorization for collaborative ranking. In NIPS, 2007.
    • (2007) NIPS
    • Weimer, M.1    Karatzoglou, A.2    Le, Q.3    Smola, A.4
  • 10
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    • Local implicit feedback mining for music recommendation
    • D. Yang, T. Chen, W. Zhang, Q. Lu, and Y. Yu. Local implicit feedback mining for music recommendation. In RecSys, 2012.
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    • Yang, D.1    Chen, T.2    Zhang, W.3    Lu, Q.4    Yu, Y.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.