E. Aguilar, F. Ruiz, F. García, and M. Piattini, Evaluation measures for business process models, Proceedings of the 2006 ACM Symposium on Applied Computing (SAC), pp.1567-1568, 2006.

J. F. Allen, Towards a general theory of action and time, Artificial Intelligence, vol.23, pp.123-154, 1984.

A. Azzini, C. Braghin, E. Damiani, and F. Zavatarelli, Using semantic lifting for improving process mining: a data loss prevention system case study, Proceedings of the 3rd International Symposium on Data-driven Process Discovery and Analysis, vol.1027, pp.62-73, 2013.

A. Azzini and P. Ceravolo, Consistent process mining over big data triple stores, IEEE International Congress on Big Data, pp.54-61, 2013.

H. Bunke, On a relation between graph edit distance and maximum common subgraph, Pattern Recognition Letters, vol.18, issue.8, p.689694, 1997.

F. Casati, M. C. Shan-;-c, K. G. Jensen, J. Jeffery, S. Pokorn´ypokorn´y et al., Semantic analysis of business process executions, Advances in Database Technology -EDBT 2002, 8th International Conference on Extending Database Technology, vol.2287, pp.287-296

. Springer, , 2002.

W. B. Croft, D. Metzler, and T. Strohman, Search Engines: Information Retrieval in Practice. Alternative Etext Formats, 2010.

A. K. Alves-de-medeiros, C. Pedrinaci, W. M. Van-der-aalst, J. Domingue, M. Song et al., An outlook on semantic business process mining and monitoring, On the Move to Meaningful Internet Systems 2007: OTM 2007 Workshops, OTM Confederated International Workshops and Posters, AWeSOMe, CAMS, OTM Academy Doctoral Consortium, vol.4806, pp.1244-1255, 2007.

A. K. Alves-de-medeiros and W. M. Van-der-aalst, Process mining towards semantics, Advances in Web Semantics I -Ontologies, vol.4891, pp.35-80, 2009.

A. K. Alves-de-medeiros, W. M. Van-der-aalst, and C. Pedrinaci, Semantic process mining tools: Core building blocks, 16th European Conference on Information Systems, pp.1953-1964, 2008.

R. Dijkman, M. Dumas, and R. Garca-banuelos, Graph matching algorithms for business process model similarity search, Proc. International Conference on Business Process Management, vol.5701, pp.48-63, 2009.

D. R. Ferreira, F. Szimanski, and C. Ghedini-ralha, Improving process models by mining mappings of low-level events to high-level activities, J. Intell. Inf. Syst, vol.43, issue.2, pp.379-407, 2014.

M. A. Grando, M. H. Schonenberg, and W. M. Van-der-aalst, Semantic process mining for the verification of medical recommendations, HEALTHINF 2011 -Proceedings of the International Conference on Health Informatics, pp.5-16, 2011.

D. Grigori, F. Casati, M. Castellanos, U. Dayal, M. Sayal et al., Business process intelligence, Computers in Industry, vol.53, issue.3, pp.321-343, 2004.
URL : https://hal.archives-ouvertes.fr/hal-00130689

C. Günther and W. Van-der-aalst, Fuzzy mining -adaptive process simplification based on multi-perspective metrics, Business Process Management, 5th International Conference, vol.4714, pp.328-343, 2007.

C. W. Günther, A. Rozinat, and W. Van-der-aalst, Activity mining by global trace segmentation, Business Process Management Workshops, vol.43, pp.128-139, 2009.

M. Hepp, F. Leymann, J. Domingue, A. Wahler, and D. Fensel, Semantic business process management: A vision towards using semantic web services for business process management, 2005 IEEE International Conference on e-Business Engineering (ICEBE 2005), pp.535-540, 2005.

M. Hepp and D. Roman, An ontology framework for semantic business process management, eOrganisation: Service-, Prozess-, MarketEngineering: 8. Internationale Tagung Wirtschaftsinformatik -Band, vol.1, pp.423-440, 2007.

W. Jareevongpiboon and P. Janecek, Ontological approach to enhance results of business process mining and analysis, Business Proc. Manag. Journal, vol.19, issue.3, pp.459-476, 2013.

M. N. De-maio, M. Salatino, and E. Aliverti, Mastering JBoss Drools 6 for Developers, 2016.

F. Mannhardt, M. De-leoni, H. A. Reijers, W. Van-der-aalst, and P. J. Toussaint, From low-level events to activities -A pattern-based approach, Business Process Management -14th International Conference, vol.9850, pp.125-141, 2016.

. Springer, , 2016.

S. Montani, G. Leonardi, S. Quaglini, A. Cavallini, and G. Micieli, Improving structural medical process comparison by exploiting domain knowledge and mined information, Artificial Intelligence in Medicine, vol.62, issue.1, pp.33-45, 2014.
DOI : 10.1016/j.artmed.2014.07.001

M. Palmer and Z. Wu, Verb Semantics for English-Chinese Translation. Machine Translation, vol.10, pp.59-92, 1995.
DOI : 10.1007/bf00997232

URL : https://repository.upenn.edu/cgi/viewcontent.cgi?article=1138&context=ircs_reports

C. Pedrinaci, J. Domingue, ;. Hepp, K. Hinkelmann, D. Karagiannis et al., Towards an ontology for process monitoring and mining, Proceedings of the Workshop on Semantic Business Process and Product Lifecycle Management SBPM 2007, held in conjunction with the 3rd European Semantic Web Conference, vol.251, 2007.

C. Pedrinaci, J. Domingue, C. Brelage, T. Van-lessen, D. Karastoyanova et al., Semantic business process management: Scaling up the management of business processes, Proceedings of the 2th IEEE International Conference on Semantic Computing (ICSC 2008), pp.546-553, 2008.

D. Sell, L. Cabral, E. Motta, J. Domingue, R. C. et al., Adding semantics to business intelligence, 16th International Workshop on Database and Expert Systems Applications (DEXA 2005, pp.543-547, 2005.
DOI : 10.1109/dexa.2005.44

A. Syamsiyah, B. Van-dongen, and W. Van-der-aalst, DB-XES: enabling process discovery in the large, Proceedings of the 6th International Symposium on Datadriven Process Discovery and Analysis
URL : https://hal.archives-ouvertes.fr/hal-01769759

N. Tax, N. Sidorova, R. Haakma, and W. Van-der-aalst, Event abstraction for process mining using supervised learning techniques, 2016.
DOI : 10.1007/978-3-319-56994-9_18

URL : http://arxiv.org/pdf/1606.07283

W. Van-der-aalst, Process Mining. Data Science in Action, 2016.

W. Van-der-aalst, B. Van-dongen, J. Herbst, L. Maruster, G. Schimm et al., Workflow mining: a survey of issues and approaches, Data and Knowledge Engineering, vol.47, pp.237-267, 2003.

W. M. Van-der-aalst, H. T. De-beer, and B. F. Van-dongen, Process mining and verification of properties: An approach based on temporal logic

M. Loyall, S. Kifer, D. Spaccapietra-;-coopis, and O. , OTM Confederated International Conferences CoopIS, DOA, and ODBASE 2005, vol.3760, pp.130-147, 2005.

B. Van-dongen, A. Alves-de-medeiros, H. Verbeek, A. Weijters, and W. Van-der-aalst, The proM framework: a new era in process mining tool support, Knowledge Mangement and its Integrative Elements, pp.444-454, 2005.

I. T. Vanderfeesten, H. A. Reijers, J. Mendling, W. M. Van-der-aalst, and J. S. Cardoso, On a quest for good process models: The cross-connectivity metric, Advanced Information Systems Engineering, 20th International Conference, vol.5074, pp.480-494, 2008.

H. M. Verbeek, J. C. Buijs, B. F. Van-dongen, and W. M. Van-der-aalst, Xes, xesame, and prom 6, Information Systems Evolution -CAiSE Forum, vol.72, pp.60-75, 2010.
DOI : 10.1007/978-3-642-17722-4_5

URL : https://link.springer.com/content/pdf/10.1007%2F978-3-642-17722-4_5.pdf

A. Weijters, W. Van-der-aalst, and A. Alves-de-medeiros, Process Mining with the Heuristic Miner Algorithm, WP 166, 2006.