L. Baltrunas and F. Ricci, Dynamic item weighting and selection for collaborative filtering, Web Mining 2.0 Workshop, ECML-PKDD, 2007.

J. S. Breese, D. Heckerman, and C. Kadie, Empirical analysis of predictive algorithms for collaborative filtering, Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence, pp.43-52, 1998.

J. L. Herlocker, J. A. Konstan, A. Borchers, and J. , An algorithmic framework for performing collaborative filtering, Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval , SIGIR '99, pp.230-237, 1999.
DOI : 10.1145/312624.312682

R. Jin, J. Y. Chai, and L. Si, An automatic weighting scheme for collaborative filtering, Proceedings of the 27th annual international conference on Research and development in information retrieval , SIGIR '04, pp.337-344, 2004.
DOI : 10.1145/1008992.1009051

M. Khoshneshin and W. N. Street, Collaborative filtering via euclidean embedding, Proceedings of the fourth ACM conference on Recommender systems, RecSys '10, 2010.
DOI : 10.1145/1864708.1864728

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

Y. Koren, Factorization meets the neighborhood, Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD 08, pp.426-434, 2008.
DOI : 10.1145/1401890.1401944

Y. Koren, Collaborative filtering with temporal dynamics, Commun. ACM, pp.89-97, 2010.
DOI : 10.1145/1721654.1721677

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

Y. Koren, R. Bell, and C. Volinsky, Matrix Factorization Techniques for Recommender Systems, Computer, vol.42, issue.8, pp.30-37, 2009.
DOI : 10.1109/MC.2009.263

G. Linden, B. Smith, and J. York, Amazon.com recommendations: item-to-item collaborative filtering, IEEE Internet Computing, vol.7, issue.1, pp.76-80, 2003.
DOI : 10.1109/MIC.2003.1167344

P. Melville, R. J. Mooney, and R. Nagarajan, Content-boosted collaborative filtering for improved recommendations, Artificial intelligence, pp.187-192, 2002.

D. M. Pennock, E. Horvitz, S. Lawrence, and C. L. Giles, Collaborative filtering by personality diagnosis: a hybrid memory-and model-based approach, In Uncertainty in artificial intelligence, pp.473-480, 2000.

A. Said, B. J. Jain, and S. Albayrak, Analyzing weighting schemes in collaborative filtering, Proceedings of the 27th Annual ACM Symposium on Applied Computing, SAC '12, pp.2035-2040, 2012.
DOI : 10.1145/2245276.2232114

R. Salakhutdinov, A. Mnih, and G. Hinton, Restricted Boltzmann machines for collaborative filtering, Proceedings of the 24th international conference on Machine learning, ICML '07, pp.791-798, 2007.
DOI : 10.1145/1273496.1273596

B. Sarwar, G. Karypis, J. Konstan, and J. , Item-based collaborative filtering recommendation algorithms, Proceedings of the tenth international conference on World Wide Web , WWW '01, pp.285-295, 2001.
DOI : 10.1145/371920.372071

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

X. Su and T. M. Khoshgoftaar, A Survey of Collaborative Filtering Techniques, Advances in Artificial Intelligence, vol.46, issue.2, pp.2-4, 2009.
DOI : 10.1002/asi.10372

P. Symeonidis, A. Nanopoulos, and Y. Manolopoulos, Feature-Weighted User Model for Recommender Systems, User Modeling, pp.97-106, 2007.
DOI : 10.1007/978-3-540-73078-1_13

D. Wettschereck, D. W. Aha, and T. Mohri, A Review and Empirical Evaluation of Feature Weighting Methods for a Class of Lazy Learning Algorithms, Artificial Intelligence Review, vol.11, pp.273-314, 1997.
DOI : 10.1007/978-94-017-2053-3_11

K. Yu, X. Xu, M. Ester, and H. Kriegel, Feature Weighting and Instance Selection for Collaborative Filtering: An Information-Theoretic Approach*, Knowledge and Information Systems, vol.5, issue.2, pp.201-224, 2003.
DOI : 10.1007/s10115-003-0089-6