J. S. Gero-]-d, L. Ullman, E. Roucoules, W. Yahia, S. Es-soufi et al., The mechanical design process Engineering design memory for design rationale and change management toward innovation Collaborative Design and Supervision Processes Meta-Model for Rationale Capitalization Process mining: overview and opportunities, Advances on Mechanics, Design Engineering and Manufacturing: Proceedings of the International Joint Conference on Mechanics, Design Engineering & Advanced Manufacturing. [5] W. van der Aalst, Process Mining: Discovery, Conformance and Enhancement of Business Processes, pp.435-448, 1996.

C. Alexander, S. Ishikawa, M. Silverstein, E. Gamma, R. Helm et al., A Pattern Language: Towns, Buildings, Construction Design Patterns: Elements of Reusable Object-Oriented Software. Pearson Education Product information systems engineering: an approach for building product models by reuse of patterns, Robotics and Computer- Integrated Manufacturing, vol.19, issue.3, pp.239-261, 1977.

Y. Kodratoff, R. S. Michalski, R. S. Michalski, J. G. Carbonell, and T. M. Mitchell, Machine Learning: An Artificial Intelligence Approach, 1990.

J. Han, M. Kamber, and J. Pei, Data Mining, 2011.
DOI : 10.1007/978-1-4899-7993-3_104-2

A. Albalate and W. Minker, Semi-Supervised and Unsupervised Machine Learning: Novel Strategies, 2013.
DOI : 10.1002/9781118557693

X. Zhu and A. B. Goldberg, Introduction to Semi-Supervised Learning, Synthesis Lectures on Artificial Intelligence and Machine Learning, vol.3, issue.1, pp.1-130, 2009.
DOI : 10.2200/S00196ED1V01Y200906AIM006

P. Kulkarni, Reinforcement and systemic machine learning for decision making, 2012.
DOI : 10.1002/9781118266502

S. K. Sim and A. H. Duffy, A foundation for machine learning in design, AI EDAM, vol.12, issue.02, pp.193-209, 1998.
DOI : 10.1017/S0890060498122096

S. S. Tong, D. Powell, and D. Cornett, ENGINEOUS: A UNIFIED METHOD FOR DESIGN AUTOMATION, OPTIMIZATION, AND INTEGRATION, Artificial intelligence in engineering design (Volume III), pp.235-254, 1992.
DOI : 10.1016/B978-0-08-092602-5.50016-0

D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, 1989.

H. Chen and H. Chang, Abstract, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, vol.63, issue.01, pp.64-77, 2016.
DOI : 10.1016/j.displa.2010.12.001

URL : https://hal.archives-ouvertes.fr/hal-00780803

P. Pitiot, T. Coudert, L. Geneste, and C. Baron, Hybridation of Bayesian networks and evolutionary algorithms for multi-objective optimization in an integrated product design and project management context, Engineering Applications of Artificial Intelligence, vol.23, issue.5, pp.830-843, 2010.
DOI : 10.1016/j.engappai.2010.01.019

URL : https://hal.archives-ouvertes.fr/hal-00758621

F. Danglade, J. Pernot, and P. Véron, On the use of Machine Learning to Defeature CAD Models for Simulation, Computer-Aided Design and Applications, vol.34, issue.2, pp.358-368, 2014.
DOI : 10.1080/16864360.2004.10738315

URL : https://hal.archives-ouvertes.fr/hal-01015339

H. S. Yan and D. Xu, An Approach to Estimating Product Design Time Based on Fuzzy \nu -Support Vector Machine, IEEE Transactions on Neural Networks, vol.18, issue.3, pp.721-731, 2007.

P. Reimann, R. Calvo, K. Yacef, and V. Southavilay, Comprehensive Computational Support for Collaborative Learning from Writing, International Conference on Computers in Education (ICCE), 2010.

M. Saravanan and R. Rama-sree, Application of mining algorithms using ProM and Weka tools, IJCST, vol.2, issue.3, 2011.

R. Crerie, F. A. Baião, and F. M. Santoro, Discovering Business Rules through Process Mining, Enterprise, Business-Process and Information Systems Modeling, pp.136-148, 2009.
DOI : 10.1007/11841760_33

B. F. Van-dongen and W. M. Van-der-aalst, A Meta Model for Process Mining Data, EMOI-INTEROP, vol.160, p.30, 2005.

R. J. Bose and W. M. Van-der-aalst, Abstractions in process mining: A taxonomy of patterns, Business Process Management, pp.159-175, 2009.

J. R. Quinlan and C. , 5: Programs for Machine Learning, 1993.