Improving Music Recommendation Using Distributed Representation-Reference-Cited by-同舟云学术

Improving Music Recommendation Using Distributed Representation

Published:2016 Issue: Volume: Page:
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Container-title:Proceedings of the 25th International Conference Companion on World Wide Web - WWW '16 Companion
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Author:

Wang Dongjing¹,Deng Shuiguang¹,Liu Songguo²,Xu Guandong³

Affiliation:

1. Zhejiang University, Hangzhou, China

2. Hangzhou National E-commerce Product Quality Monitoring and Management Center, Hangzhou, China

3. University of Technology Sydney, Sydney, Australia

Funder

National Key Technology Research and Development Program of China

Publisher

ACM Press

Reference6 articles.

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2. S. Rendle, C. Freudenthaler, Z. Gantner, and L. Schmidt-Thieme, BPR: Bayesian personalized ranking from implicit feedback. In Proceedings of the 25th Conference on Uncertainty in Artificial Intelligence, 452--461, 2009.

3. S. Kabbur, X. Ning, and G. Karypis, Fism: factored item similarity models for top-n recommender systems. In Proceedings of the 19th ACM international conference on Knowledge discovery and data mining, 659--667, 2013.

4. P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, and J. Riedl, GroupLens: an open architecture for collaborative filtering of netnews. In Proceedings of the ACM conference on Computer supported cooperative work, 175--186, 1994.

5. S. Deng, L. Huang, and G. Xu. Social network-based service recommendation with trust enhancement. Expert Systems with Applications, 41, 18 (12/15/), 8075--8084, 2014.

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