P. Auer, Using confidence bounds for exploitationexploration trade-offs, Journal of Machine Learning Research, vol.3, pp.397-422, 2002.

A. Barabasi, A. , and R. , Emergence of scaling in random networks, Science, vol.286, p.11, 1999.

M. Belkin, I. Matveeva, and P. Niyogi, Regularization and Semi-Supervised Learning on Large Graphs, Conference on Learning Theory, 2004.

M. Belkin, P. Niyogi, and V. Sindhwani, Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples, Journal of Machine Learning Research, vol.7, pp.2399-2434, 2006.

D. Billsus, M. J. Pazzani, C. , and J. , A learning agent for wireless news access, Proceedings of the 5th international conference on Intelligent user interfaces , IUI '00, pp.33-36, 2000.
DOI : 10.1145/325737.325768

D. Jannach, M. Zanker, A. Felfernig, and G. Friedrich, Recommender Systems: An Introduction, 2010.
DOI : 10.1017/CBO9780511763113

T. Kocák, M. Valko, R. Munos, and S. Agrawal, Spectral Thompson Sampling, Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelli- gence, 2014.

I. Koutis, G. L. Miller, and R. Peng, Approaching Optimality for Solving SDD Linear Systems, 2010 IEEE 51st Annual Symposium on Foundations of Computer Science, pp.235-244, 2010.

L. Li, W. Chu, J. Langford, and R. E. Schapire, A contextual-bandit approach to personalized news article recommendation, Proceedings of the 19th international conference on World wide web, WWW '10, 2010.
DOI : 10.1145/1772690.1772758

M. Mcpherson, L. Smith-lovin, and J. Cook, Birds of a Feather: Homophily in Social Networks, Annual Review of Sociology, vol.27, issue.1, pp.415-444, 2001.
DOI : 10.1146/annurev.soc.27.1.415

M. J. Pazzani and D. Billsus, Content-Based Recommendation Systems. The adaptive web, 2007.

M. Valko, R. Munos, B. Kveton, and T. Kocák, Spectral Bandits for Smooth Graph Functions, 31th International Conference on Machine Learning, 2014.
URL : https://hal.archives-ouvertes.fr/hal-00986818

X. Zhu, Semi-Supervised Learning Literature Survey, 2008.