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Volumn , Issue , 2014, Pages 89-96

Item cold-start recommendations: Learning local collective embeddings

Author keywords

[No Author keywords available]

Indexed keywords

EMBEDDINGS; FACTORIZATION; RECOMMENDER SYSTEMS;

EID: 84908866544     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2645710.2645751     Document Type: Conference Paper
Times cited : (190)

References (29)
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    • (2005) IEEE Transactions on Knowledge and Data Engineering , vol.17 , Issue.6 , pp. 734-749
    • Adomavicius, G.1    Tuzhilin, A.2
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    • 0043278893 scopus 로고    scopus 로고
    • Laplacian eigenmaps and spectral techniques for embedding and clustering
    • M. Belkin and P. Niyogi. Laplacian eigenmaps and spectral techniques for embedding and clustering. In Advances in Neural Information Processing Systems, volume 14, pages 585-591, 2001.
    • (2001) Advances in Neural Information Processing Systems , vol.14 , pp. 585-591
    • Belkin, M.1    Niyogi, P.2
  • 9
    • 33750729556 scopus 로고    scopus 로고
    • Manifold regularization: A geometric framework for learning from labeled and unlabeled examples
    • M. Belkin, P. Niyogi, and V. Sindhwani. Manifold regularization: A geometric framework for learning from labeled and unlabeled examples. Journal of Machine Learning Research, 7(2006):2399-2434, 2006.
    • (2006) Journal of Machine Learning Research , vol.7 , Issue.2006 , pp. 2399-2434
    • Belkin, M.1    Niyogi, P.2    Sindhwani, V.3
  • 14
    • 29644438050 scopus 로고    scopus 로고
    • Statistical comparison of classiers over multiple data sets
    • J. Demsar. Statistical Comparison of Classiers over Multiple Data Sets. Journal of Machine Learning Research, 7:1-30, 2006.
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    • Demsar, J.1
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    • Latent class models for collaborative filtering
    • T. Hofmann and J. Puzicha. Latent Class Models for Collaborative Filtering. Machine Learning, 16:688-693, 1999.
    • (1999) Machine Learning , vol.16 , pp. 688-693
    • Hofmann, T.1    Puzicha, J.2
  • 20
    • 85008044987 scopus 로고    scopus 로고
    • Matrix factorization techniques for recommender systems
    • Y. Koren, R. Bell, and C. Volinsky. Matrix factorization techniques for recommender systems. Computer, 42:30-37, 2009.
    • (2009) Computer , vol.42 , pp. 30-37
    • Koren, Y.1    Bell, R.2    Volinsky, C.3
  • 22
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
    • D. Lee and S. Seung. Learning the parts of objects by non-negative matrix factorization. Nature, 401:788-791, 1999.
    • (1999) Nature , vol.401 , pp. 788-791
    • Lee, D.1    Seung, S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.