G. Adomavicius and A. Tuzhilin, Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions, IEEE Transactions on Knowledge and Data Engineering, vol.17, issue.6, pp.734-749, 2005.
DOI : 10.1109/TKDE.2005.99

A. Bouza, MO -the Movie Ontology | Leverage Your Movie Information, 2010.

J. G. Breslin, A. Passant, D. Vrande?i?, and D. , Social Semantic Web, Handbook of Semantic Web Technologies, pp.467-506, 2011.

E. Cambria, J. Fu, F. Bisio, and P. Poria, AffectiveSpace 2: Enabling Affective Intuition for Concept-Level Sentiment Analysis, Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI'15). AAAI, pp.508-514, 2015.
DOI : 10.1145/2567948.2577268

G. M. Edelman and G. Tononi, A Universe of Consciousness: How Matter Becomes Imagination Basic Books -274 pages Gruber, T Collective Knowledge Systems: Where the Social Web Meets the Semantic Web, Web Semantics: Science, Services and Agents on the World Wide Web, vol.6, issue.1, pp.4-13, 2000.

S. Harispe, S. Ranwez, S. Janaqi, and J. Montmain, The semantic measures library and toolkit: fast computation of semantic similarity and relatedness using biomedical ontologies, Bioinformatics, vol.30, issue.5, pp.30-740, 2014.
DOI : 10.1093/bioinformatics/btt581
URL : https://hal.archives-ouvertes.fr/hal-01059329

A. S. Harpale and Y. Yiming, Personalized active learning for collaborative filtering, Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, SIGIR '08, 2008.
DOI : 10.1145/1390334.1390352
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.142.2624

J. Hendler, N. Shadbolt, W. Hall, T. Berners-lee, and D. Weitzner, Web science, Communications of the ACM, vol.51, issue.7, pp.60-69, 2008.
DOI : 10.1145/1364782.1364798
URL : http://dl.acm.org/ft_gateway.cfm?id=1364798&type=pdf

J. J. Jung, Attribute selection-based recommendation framework for short-head user group: An empirical study by MovieLens and IMDB, Expert Systems with Applications, vol.39, issue.4, pp.4049-4054, 2012.
DOI : 10.1016/j.eswa.2011.09.096

S. Karapiperis and D. Apostolou, Consensus Building in Collaborative Ontology Engineering Processes, Journal of Universal Knowledge Management, pp.199-216, 2006.

H. L. Kim and S. Scerri, The State of the Art in Tag Ontologies: A Semantic Model for Tagging and Folksonomies, 2008.

G. J. Klir, . W-n, N. Shah, K. Sundlass, and M. Musen, Uncertainty and Information: Foundations of Generalized Information Theory Comparison of Ontology-Based Semantic-Similarity Measures. AMIA, Annual Symposium, pp.384-388, 2005.
DOI : 10.1002/0471755575

B. Markines, C. Cattuto, F. Menczer, D. Benz, A. Hotho et al., Evaluating similarity measures for emergent semantics of social tagging, Proceedings of the 18th international conference on World wide web, WWW '09, pp.641-50, 2009.
DOI : 10.1145/1526709.1526796

P. Mika, Ontologies are us: A unified model of social networks and semantics, Web Semantics: Science, Services and Agents on the World Wide Web, vol.5, issue.1, pp.5-15, 2007.
DOI : 10.1016/j.websem.2006.11.002

O. Reilly and T. , What Is Web 2.0: Design Patterns and Business Models for the Next Generation of Software, 2015.

V. Peralta, Extraction and Integration of Movielens and Imdb Data, Laboratoire Prisme, 2007.

S. Seung, L. Specia, and E. Motta, Connectome: How the Brain's Wiring Makes Us Who We Are. Houghton Mifflin Harcourt Integrating Folksonomies with the Semantic Web, ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications. Pages, pp.624-639, 2007.

H. Yamaba, T. Tanoue, and K. Takatsuka, On a serendipity-oriented recommender system based on folksonomy, Artificial Life and Robotics, vol.47, issue.5, pp.89-94, 2013.
DOI : 10.1145/963770.963772

G. Zhu and C. A. Iglesias, Computing Semantic Similarity of Concepts in Knowledge Graphs, IEEE Transactions on Knowledge and Data Engineering, vol.29, issue.1, pp.72-85, 2017.
DOI : 10.1109/TKDE.2016.2610428