Measure prediction capability of data for collaborative filtering

Author:

Liang Xijun,Xia Zhonghang,Pang Liping,Zhang Liwei,Zhang Hongwei

Funder

National Natural Science Foundation of China

National Natural Science Foundation of China (CN)

Natural Science Foundation of Shandong Province

Fundamental Research Funds for the Central Universities

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software

Reference46 articles.

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2. Adomavicius G, Tuzhilin A (2005) Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. Knowl Data Eng IEEE Trans 17(6):734–749

3. Bell R, Koren Y, Volinsky C (2007) Modeling relationships at multiple scales to improve accuracy of large recommender systems. In: Proceedings of the 13th ACM SIGKDD international conference on knowledge discovery and data mining, pp 95–104

4. Bell RM, Koren Y, Volinsky C (2008) The bellkor 2008 solution to the netflix prize. Statistics Research Department at AT&T Research

5. Breese JS, Heckerman D, Kadie C, et al (1998) Empirical analysis of predictive algorithms for collaborative filtering. In: Proceedings of the 14th conference on Uncertainty in Artificial Intelligence, pp 43–52

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