Illuminating Recommendation by Understanding the Explicit Item Relations-Reference-Cited by-同舟云学术

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Illuminating Recommendation by Understanding the Explicit Item Relations

Published:2018-07 Issue:4 Volume:33 Page:739-755
ISSN:1000-9000
Container-title:Journal of Computer Science and Technology
language:en
Short-container-title:J. Comput. Sci. Technol.

Author:

Liu Qi,Zhao Hong-Ke,Wu Le,Li Zhi,Chen En-Hong

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,Computer Science Applications,Hardware and Architecture,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s11390-018-1853-0.pdf

Reference114 articles.

1. Adomavicius G, Tuzhilin A. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering, 2005, 17(6): 734-749.

2. Ricci F, Rokach L, Shapira B. Introduction to recommender systems handbook. In Recommender Systems Handbook, Ricci F, Rokach L, Shapira B, Kantor P B (eds.), Springer, 2011, pp.1-35.

3. Lops P, de Gemmis M, Semeraro G. Content-based recommender systems: State of the art and trends. In Recommender Systems Handbook, Ricci F, Rokach L, Shapira B, Kantor P B (eds.), Springer US, 2011, pp.73-105.

4. Herlocker J L, Konstan J A, Terveen L G, Riedl J T. Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems, 2004, 22(1): 5-53.

5. Burke R. Hybrid recommender systems: Survey and experiments. User Modeling and User-Adapted Interaction, 2002, 12(4): 331-370.

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