S. Basu, I. Davidson, and K. Wagstaff, Constrained clustering: Advances in algorithms, theory, and applications, 2008.

D. Vincent, J. Blondel, R. Guillaume, E. Lambiotte, and . Lefebvre, Fast unfolding of communities in large networks, Journal of statistical mechanics: theory and experiment, issue.10, p.10008, 2008.

H. L. Bodlaender, A tourist guide through treewidth, Acta Cybernetica, vol.11, issue.1-2, pp.1-22, 1993.

M. Chabert and C. Solnon, Constraint programming for multi-criteria conceptual clustering, CP 2017, pp.460-476, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01544239

R. Chattopadhyay, W. Fan, I. Davidson, S. Panchanathan, and J. Ye, Joint transfer and batch-mode active learning, International Conference on Machine Learning, pp.253-261, 2013.

I. Davidson, Knowledge driven dimension reduction for clustering, IJCAI, pp.1034-1039, 2009.

I. Davidson and S. S. Ravi, The complexity of non-hierarchical clustering with instance and cluster level constraints, Data Min. Knowl. Discov, vol.14, issue.1, pp.25-61, 2007.

M. Ester, H. Kriegel, J. Sander, and X. Xu, A density-based algorithm for discovering clusters in large spatial databases with noise, Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), pp.226-231, 1996.

H. Douglas and . Fisher, Knowledge acquisition via incremental conceptual clustering, Machine learning, vol.2, pp.139-172, 1987.

M. R. Garey and D. S. Johnson, Computers and Intractability: A Guide to the Theory of NP-completeness, 1979.

H. John, P. Gennari, D. Langley, and . Fisher, Models of incremental concept formation, Artificial intelligence, vol.40, issue.1-3, pp.11-61, 1989.

S. Gilpin, T. Eliassi-rad, and I. Davidson, Guided learning for role discovery (GLRD): framework, algorithms, and applications, Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, pp.113-121, 2013.

T. Guns, Siegfried Nijssen, and Luc De Raedt. k-Pattern set mining under constraints, IEEE Transactions on Knowledge and Data Engineering, vol.25, issue.2, pp.402-418, 2013.

S. Jha, L. Kruger, and P. Mcdaniel, Privacy preserving clustering, European Symposium on Research in Computer Security, pp.397-417, 2005.

L. Kotthoff, B. O. Sullivan, S. S. Ravi, and I. Davidson, Complex clustering using constraint programming: Modeling electoral map creation, Proc. 14th International Workshop on Constraint Modeling and Reformulation, pp.1-14, 2015.

P. Langley, Elements of machine learning, 1996.

J. Métivier, P. Boizumault, B. Crémilleux, M. Khiari, and S. Loudni, Constrained Clustering Using SAT, Proc. Advances in Intelligent Data Analysis (IDA), pp.207-218, 2012.

M. Mueller and S. Kramer, Integer Linear Programming Models for Constrained Clustering, Proc. Discovery Science, pp.159-173, 2010.

A. Ouali, S. Loudni, Y. Lebbah, P. Boizumault, A. Zimmermann et al., Efficiently finding conceptual clustering models with integer linear programming, IJCAI'16, pp.647-654, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01597804

B. Qian and I. Davidson, Semi-supervised dimension reduction for multi-label classification, AAAI, vol.10, pp.569-574, 2010.

B. Peter, . Walker, N. Jacob, A. E. Norris, M. L. Tschiffely et al., Applications of transductive spectral clustering methods in a military medical concussion database, IEEE/ACM transactions on computational biology and bioinformatics, vol.14, issue.3, pp.534-544, 2017.

X. Wang, B. Qian, J. Ye, and I. Davidson, Multi-objective multi-view spectral clustering via Pareto optimization, Proceedings of the 2013 SIAM International Conference on Data Mining, pp.234-242, 2013.