Seminal Articles in Recommender System

  1. P. Resnick, N. Iacovou, M. Suchak, P. Bergstrom, J. Riedl, GroupLens: an open architecture for collaborative filtering of netnews, in: Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work, 1994, pp. 175– 186.

  2. J. Bobadilla, F. Ortega, A. Hernando, A. Gutirrez, Recommender systems survey, Knowl.-Based Syst. 46 (2013) 109–132.

  3. J.L. Herlocker, J.A. Konstan, L.G. Terveen, J.T. Riedl, Evaluating collaborative filtering recommender systems, ACM Trans. Inf. Syst. 22 (1) (2004) 5–53.

  4. ]. C. Desrosiers, G. Karypis, A comprehensive survey of neighborhood-based recommendation methods, in: Recommender Systems Handbook, 2011, pp. 107–144.

  5. B. Sarwar, G. Karypis, J. Konstan, J. Riedl, Item-based collaborative filtering recommendation algorithms, in: Proceedings of the 10th International Conference on World Wide Web, 2001, pp. 285–295. (Article)

  6. M.D. Ekstrand, J.T. Riedl, J.A. Konstan, Collaborative filtering recommender systems, Found. Trends Human–Comput. Interact. 4 (2) (2011) 81–173.

  7. G. Karypis, Evaluation of item-based top-N recommendation algorithms, in: Proceedings of the Tenth International Conference on Information and Knowledge Management, 2001, pp. 247–254.

  8. A. Paterek, Improving regularized singular value decomposition for collaborative filtering, in: Proceeding of KDD Cup Workshop at 13th ACM Int. Conf. on Knowledge Discovery and Data Mining, 2007, pp. 39–42

  9. Y. Koren, Factor in the neighbors: scalable and accurate collaborative filtering, ACM Trans. Knowl. Discov. Data 4 (1) (2010) 1:1–1:24.

  10. Y. Koren, Factorization meets the neighborhood: a multifaceted collaborative filtering model, in: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008, pp. 426–434.

  11. Yehuda Koren, Robert Bell, and Chris Volinsky. 2009. Matrix Factorization Techniques for Recommender Systems. Computer 42, 8 (August 2009), 30-37.