A. R. Srikant-r, Fast algorithms for mining association rules in large databases, 1994.

B. H. Haddad-m and . B. Ghezala-h, A personalised semantic and spatial information retrieval system based on user's modelling and accessibility measure, International Journal of Multicriteria Decision Making, vol.4, issue.2, pp.183-200, 2014.

B. Balabanovi´c and M. &. Shoham-y, Fab: content-based, collaborative recommendation, Communications of the ACM, vol.40, issue.3, pp.66-72, 1997.
DOI : 10.1145/245108.245124

B. S. Ziou-d, A graphical model for context-aware visual content recommendation, IEEE Transactions on Multimedia, vol.10, issue.1, pp.52-62, 2008.

D. M. Karypis-g, Recommendation Algorithms, Proceedings of the tenth international conference on Information and knowledge management , CIKM'01, pp.143-177, 2004.
DOI : 10.1145/502585.502627

G. D. , N. D. Oki-b, and . Terry-d, Using collaborative filtering to weave an information tapestry, Communications of the ACM, vol.35, issue.12, pp.61-70, 1992.

H. D. Best-r and . A. Coney-k, Consumer Behavior : Building Marketing Strategy, 2003.

H. Liao, S. Hui, C. P. Ju, C. Y. , and C. , Mining customer knowledge for exploring online group buying behavior, Expert Systems with Applications, vol.39, issue.3, pp.3708-3716, 2012.
DOI : 10.1016/j.eswa.2011.09.066

I. S. Lepper-m, When choice is demotivating : can one desire too much of a good thing, Journal of Personality and Social Psychology, vol.79, issue.6, pp.995-1006, 2000.

J. J. and S. D. Berning-c, Brand choice behavior as a function of information load : Replication and extension, Journal of Consumer Research : An Interdisciplinary Quarterly, vol.1, issue.1, pp.33-42, 1974.

L. W. Alvarez-s and . Ruiz-c, Efficient adaptive-support association rule mining for recommender systems, Data Min. Knowl. Discov, vol.6, issue.1, pp.83-105, 2002.

L. G. and S. B. York-j, Amazon.com recommendations : Item-to-item collaborative filtering, IEEE Internet Computing, vol.7, issue.1, pp.76-80, 2003.

M. R. Roy-l, Content-based book recommending using learning for text categorization, Proceedings of the Fifth ACM Conference on Digital Libraries, pp.195-204, 2000.

P. M. Guardia-sebaoun and G. V. Gallinari-p, Recommandation par combinaison de filtrage collaboratif et d'analyse de sentiments, CORIA-CIFED, pp.27-42, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00965405

R. P. Iacovou-n, . Suchak-m, . Bergstorm-p, and . Riedl-j, Grouplens : An open architecture for collaborative filtering of netnews, Proceedings of ACM 1994 Conference on Computer Supported Cooperative Work, pp.175-186, 1994.

S. B. Karypis-g and K. J. Riedl-j, Item-based collaborative filtering recommendation algorithms, WWW, pp.285-295, 2001.

W. W. Groh-g, Utilizing physical and social context to improve recommender systems, Web Intelligence/IAT Workshops, pp.123-128, 2007.

Z. Y. , Q. J. , and S. H. Cao-j, Personalized product recommendation based on customer value hierarchy, SMC, pp.3250-3254, 2007.