Data Sparsity Issues in the Collaborative Filtering Framework

Author:

Grčar Miha,Mladenič Dunja,Fortuna Blaž,Grobelnik Marko

Publisher

Springer Berlin Heidelberg

Reference19 articles.

1. Aggarwal, C.C., Wolf, J.L., Wu, K.-L., Yu, P.S.: Horting hatches an egg: A new graph-theoretic approach to collaborative filtering. In: Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (1999)

2. Baldi, P., Frasconi, P., Smyth, P.: Modeling the Internet and the Web: Probabilistic Methods and Algorithms. Wiley, New York (2003)

3. Billsus, D., Pazzani, M.J.: Learning collaborative information filers. In: Proceedings of the 15th International Conference on Machine Learning (1998)

4. Breese, J.S., Heckerman, D., Kadie, C.: Empirical analysis of predictive algorithms for collaborative filtering. In: Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence (1998)

5. Chang, C.-C., Lin, C.-J.: LibSvm: A Library for Support Vector Machines (2001), Software available at http://www.csie.ntu.edu.tw/

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