J. Abernethy, O. Chapelle, C. Castillo, and «. Witch, A New Approach to Web Spam Detection, Proceedings of the 4th International Workshop on Adversarial Information Retrieval on the Web (AIRWeb, 2008.

R. Angelova, G. Kasneci, G. Weikum, and . Graffiti, Graffiti: graph-based classification in heterogeneous networks, World Wide Web, vol.5, issue.1, pp.2-2, 2012.
DOI : 10.1007/s11280-011-0126-4

M. Belkin, P. Niyogi, V. Sindhwani, and . Manifold, Regularization : A Geometric Framework for Learning from Labeled and Unlabeled Examples, J. Mach. Learn. Res, vol.7, pp.2399-2434, 2006.

L. Denoyer and P. Gallinari, Ranking Based Model for Automatic Image Annotation in a Social Network, 2010.

T. Hwang and R. Kuang, A Heterogeneous Label Propagation Algorithm for Disease Gene Discovery, p.12, 2010.
DOI : 10.1137/1.9781611972801.51

Z. Kou, Stacked Graphical Models for Efficient Inference in Markov Random Fields, Proceedings of the 2007 SIAM International Conference on Data Mining, 2007.
DOI : 10.1137/1.9781611972771.57

F. Maes, S. Peters, L. Denoyer, and P. Gallinari, Simulated Iterative Classification A New Learning Procedure for Graph Labeling, Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases Part II, pp.47-62, 2009.
DOI : 10.1007/978-3-642-04174-7_4

Y. Sun, Y. Yu, and J. Han, Ranking-based clustering of heterogeneous information networks with star network schema, Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '09, pp.797-806, 2009.
DOI : 10.1145/1557019.1557107

J. Weston, F. Ratle, and R. Collobert, Deep learning via semi-supervised embedding, pp.1168-1175, 2008.
DOI : 10.1145/1390156.1390303

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.149.8587

D. Zhou, O. Bousquet, T. N. Lal, J. Weston, and B. Schölkopf, « Learning with Local and Global Consistency, Advances in Neural Information Processing Systems, 2004.

D. Zhou, J. Huang, and B. Schölkopf, Learning from labeled and unlabeled data on a directed graph, Proceedings of the 22nd international conference on Machine learning , ICML '05, pp.1036-1043, 2005.
DOI : 10.1145/1102351.1102482