R. Agrawal, D. Gunopulos, and F. Leymann, Mining process models from workflow logs, pp.98-469, 1998.
DOI : 10.1007/BFb0101003

R. Agrawal and R. Srikant, Mining sequential patterns, Proceedings of the Eleventh International Conference on Data Engineering, pp.95-98, 1995.
DOI : 10.1109/ICDE.1995.380415

O. Arnold and . Allen, Probability, statistics and queueing theory, with computer science applications, 1978.

J. F. Allen, Maintaining knowledge about temporal intervals, Communications of the ACM, vol.26, issue.11, pp.832-843, 1983.
DOI : 10.1145/182.358434

H. Amaury, Modeles et techniques en inference grammaticale probabiliste : de la gestion du bruit a lÕextraction de connaissances, p.147, 2004.

A. Arkin, S. Askary, S. Fordin, W. Jekeli, K. Kawaguchi et al., Web service choreography interface (wsci) 1.0, W3C Note, 2002.

D. Austin, A. Barbir, C. Ferris, and S. Garg, Web services ar- chitecture requirements, W3C Working Group Note, 2004.

A. Barros, M. Dumas, and P. Oaks, A critical overview of the web service choreography description language

A. Barros, M. Dumas, and A. H. Ter-hofstede, Service interaction patterns, Business Process Management, pp.302-318, 2005.

C. Bartolini, C. Stefanelli, and M. Tortonesi, Symian: A simulation tool for the optimization of the it incident management process, DSOM '08: Proceedings of the 19th IFIP, Distributed Systems: Operations and Management, pp.83-94, 2008.

C. Beeri, A. Eyal, T. Milo, and A. Pilberg, Monitoring business processes with queries, Proceedings of the 33rd international conference on Very large data bases, VLDB Endowment, pp.603-614, 2007.

R. Bellazzi, C. Larizza, and P. Magni, Temporal data mining for the quality assessment of hemodialysis services, Artificial Intelligence in Medicine, vol.34, issue.1, pp.25-39, 2005.
DOI : 10.1016/j.artmed.2004.07.010

B. Benatallah, F. Casati, J. Ponge, and F. Toumani, Compatibility and replaceability analysis for timed web service protocols, 2005.

B. Benatallah, F. Casati, and F. Toumani, Analysis and management of web service protocols, Conceptual Modeling -ER '04, pp.524-541, 2004.

B. Benatallah, F. Casati, F. Toumani, J. Ponge, and H. R. Nezhad, Service Mosaic: A Model-Driven Framework for Web Services Life-Cycle Management, IEEE Internet Computing, vol.10, issue.4, pp.55-63, 2006.
DOI : 10.1109/MIC.2006.87

D. Berardi, Automatic composition services: Models, techniques and tools, 2005.

D. Beyer, A. Chakrabarti, and T. A. Henzinger, Web service interfaces, Proceedings of the 14th international conference on World Wide Web , WWW '05, pp.148-159, 2005.
DOI : 10.1145/1060745.1060770

A. W. Biermann and J. A. Feldman, On the Synthesis of Finite-State Machines from Samples of Their Behavior, IEEE Transactions on Computers, vol.21, issue.6, pp.592-597, 1972.
DOI : 10.1109/TC.1972.5009015

D. Box, D. Ehnebuske, G. Kakivaya, and L. Andrew, Simple object access protocol (soap) 1.1. w3c note, 2000.

A. Brogi, C. Canal, E. Pimentel, and A. Vallecillo, Formalizing Web Service Choreographies, Electronic Notes in Theoretical Computer Science, vol.105, pp.73-94, 2004.
DOI : 10.1016/j.entcs.2004.05.007

C. Bussler, B2b integration: Concepts and architecture, 2003.
DOI : 10.1007/978-3-662-05169-6

J. Cámara, C. Canal, J. Cubo, and A. Vallecillo, Formalizing wsbpel business processes using process algebra, Electron. Notes Theor. Comput

J. Carmona, J. Cortadella, and M. Kishinevsky, Divide-and-Conquer Strategies for Process Mining, BPM '09: Proceedings of the 7th International Conference on Business Process Management, pp.327-343, 2009.
DOI : 10.1007/978-3-540-68746-7_24

F. Casati, M. Castellanos, U. Dayal, and N. Salazar, A generic solution for warehousing business process data, VLDB '07: Proceedings of the 33rd international conference on Very large data bases, VLDB Endowment, pp.1128-1137, 2007.

M. Castellanos, F. Casati, M. Shan, and U. Dayal, iBOM: A Platform for Intelligent Business Operation Management, 21st International Conference on Data Engineering (ICDE'05), pp.1084-1095, 2005.
DOI : 10.1109/ICDE.2005.73

. Centre, Service management framework

S. Chatterjee and A. S. Hadi, Regression analysis by example, pp.21-50, 2000.
DOI : 10.1002/0470055464

E. Christensen, F. Curbera, G. Meredith, and S. Weerawarana, Web services description language (wsdl) 1.1, W3C Working Group Note, 2001.

J. Chung, K. Lin, and R. G. Mathieu, Web services computing: advancing software interoperability, Computer, vol.36, issue.10, pp.35-37, 2003.
DOI : 10.1109/MC.2003.1236469

R. Paul and . Cohen, Fluent learning: Elucidating the structure of episodes, IDA' 01: 4th International Conference on Advances in Intelligent Data Analysis, pp.268-277, 2001.

W. W. Cohen, Fast Effective Rule Induction, Proceedings of the 12th International Conference on Machine Learning, pp.115-123, 1995.
DOI : 10.1016/B978-1-55860-377-6.50023-2

A. Colombo, E. Damiani, and G. Gianini, Discovering the software process by means of stochastic workflow analysis, Journal of Systems Architecture, vol.52, issue.11, pp.684-692, 2006.
DOI : 10.1016/j.sysarc.2006.06.012

J. E. Cook and A. L. Wolf, Automating process discovery through event-data analysis, Proceedings of the 17th international conference on Software engineering , ICSE '95, pp.73-82, 1995.
DOI : 10.1145/225014.225021

J. E. Cook and A. L. Wolf, Discovering models of software processes from event-based data, ACM Transactions on Software Engineering and Methodology, vol.7, issue.3, pp.215-249, 1998.
DOI : 10.1145/287000.287001

F. Curbera, R. Khalaf, N. Mukhi, S. Tai, and S. Weerawarana, The next step in Web services, Communications of the ACM, vol.46, issue.10, pp.29-34, 2003.
DOI : 10.1145/944217.944234

S. Das and M. C. Mozer, A unified gradient-descent/clustering architecture for finite state machine induction, Advances in Neural Information Processing Systems, vol.6, pp.19-26, 1994.

H. Thomas and . Davenport, Process innovation: reengineering work through information technology, 1993.

B. David and C. Michael, Ferris Chris, and McCabe Fran- cis, Web services architecture, W3C Working Draft Available at http://www.w3, 2003.

C. De and L. Higuera, A bibliographical study of grammatical inference, Pattern Recogn, pp.1332-1348, 2005.

A. K. De-medeiros, M. P. Wil, A. J. Van-der-aalst, and . Weijters, Workflow Mining: Current Status and Future Directions, Lecture Notes in Computer Science, vol.2888, pp.389-406, 2003.
DOI : 10.1007/978-3-540-39964-3_25

M. Wim-de-pauw, E. Lei, L. Pring, M. Villard, J. F. Arnold et al., Web services navigator: visualizing the execution of web services, IBM Syst, J, vol.44, issue.4, pp.821-845, 2005.

T. Debevoise, Business process management with a business rules approach: Implementing the service oriented architecture, 2007.

G. Decker, O. Kopp, and A. Barros, An introduction to service choreographies, Information Technology, vol.50, issue.2, pp.122-127, 2008.

G. Decker, O. Kopp, F. Leymann, and M. Weske, BPEL4Chor: Extending BPEL for Modeling Choreographies, IEEE International Conference on Web Services (ICWS 2007), pp.296-303, 2007.
DOI : 10.1109/ICWS.2007.59

G. Denaro, M. Pezzé, D. Tosi, and D. Schilling, Towards self-adaptive service-oriented architectures, Proceedings of the 2006 workshop on Testing, analysis, and verification of web services and applications , TAV-WEB '06, pp.10-16, 2006.
DOI : 10.1145/1145718.1145720

N. Desai, A. U. Mallya, A. K. Chopra, and M. P. Singh, Interaction protocols as design abstractions for business processes, IEEE Transactions on Software Engineering, vol.31, issue.12
DOI : 10.1109/TSE.2005.140

D. Devaurs and K. Musaraj, Fabien De Marchi, and Mohand Said Hacid, Timed transition discovery from web service conversation logs, 20th International Conference on Advanced Information Systems Engineering (CAISE'08)

J. Diane and E. John, Web services business process execution language version 2.0, OASIS Standard, 2007.

S. Dustdar and R. Gombotz, Discovering web service workflows using web services interaction mining, International Journal of Business Process Integration and Management, vol.1, issue.4, pp.256-266, 2006.
DOI : 10.1504/IJBPIM.2006.012624

S. Dustdar, R. Gombotz, and K. Baïna, Web services interaction mining, 2004.

S. Dustdar and W. Schreiner, A survey on web services composition, International Journal of Web and Grid Services, vol.1, issue.1, pp.1-30, 2005.
DOI : 10.1504/IJWGS.2005.007545

A. L. Edwards, Introduction to linear regression and correlation, pp.20-32, 1976.

C. A. Ellis, Formal and informal models of office activity, Information Processing, pp.11-22, 1983.

R. John, F. , and S. Myra, A survey of temporal knowledge discovery paradigms and methods, IEEE Trans. on Knowl. and Data Eng, vol.14, issue.4, pp.750-767, 2002.

M. Usama, G. Fayyad, P. Piatetsky-shapiro, and . Smyth, From data mining to knowledge discovery: an overview, American Association for Artificial Intelligence, pp.1-34, 1996.

R. Diogo, D. Ferreira, and . Gillblad, Discovering process models from unlabelled event logs, Proceedings of the 7th International Conference on Business Process Management, pp.143-158, 2009.

R. Thomas and F. , Architectural styles and the design of network-based software architectures, 2000.

D. Georgakopoulos, M. Hornick, and A. Sheth, An overview of workflow management: From process modeling to workflow automation infrastructure , DISTRIBUTED AND PARALLEL DATABASES, pp.119-153, 1995.

M. Goebel and L. Gruenwald, A survey of data mining and knowledge discovery software tools, ACM SIGKDD Explorations Newsletter, vol.1, issue.1, pp.20-33, 1999.
DOI : 10.1145/846170.846172

B. Goethals, Survey on frequent pattern mining, Manuscript, 2003.

G. Greco, A. Guzzo, G. Manco, and D. Saccà, Mining and reasoning on workflows, IEEE Transactions on Knowledge and Data Engineering, vol.17, issue.4, pp.519-534, 2005.
DOI : 10.1109/TKDE.2005.63

C. Gu, Y. Hui-you-chang, and . Yi, and Sun Yat-sen, Overview of workflow mining technology, GRC '07: IEEE International Conference on Granular Computing, pp.347-347, 2007.

R. Hamadi and B. Benatallah, A petri net-based model for web service composition, ADC '03: Proceedings of the 14th Australasian database conference, pp.191-200, 2003.

. Hewlett-packard, Hp openview solutions, 2010.

D. Hollingsworth, The workflow reference model, 1995.

F. Höppner and T. Braunschweig, Knowledge discovery from sequential data, 2003.

F. Höppner and F. Klawonn, Finding informative rules in interval sequences , Intelligent Data Analysis Int, Journal, vol.6, pp.237-256, 2002.

H. Hu, Z. Li, and A. Wang, Mining of Flexible Manufacturing System Using Work Event Logs and Petri Nets, ADMA '06: 2nd International Conference Advanced Data Mining and Applications, pp.380-387, 2006.
DOI : 10.1007/11811305_42

. San-yih, W. Hwang, and . Yang, On the discovery of process models from their instances, Decision Support Systems, vol.34, issue.1, pp.41-57, 2002.

C. F. Ilse and . Ipsen, Numerical matrix analysis: Linear systems and least squares, 2009.

R. P. , C. Bose, M. P. Wil, and . Van-der-aalst, Abstractions in process mining: A taxonomy of patterns, BPM '09: Proceedings of the 7th International Conference on Business Process Management, pp.159-175, 2009.

P. Kam and A. Fu, Discovering temporal patterns for intervalbased events, Proceedings of the 2nd International Conference on Data Warehousing and Knowledge Discovery (DaWaKÕ00, pp.317-326, 2000.

B. Karim, B. Boualem, C. Fabio, and T. Farouk, Modeldriven web service development, Proceedings of the 16th IntÕl Conf. Advanced Information Systems Engineering, pp.290-306, 2004.

N. Kavantzas, D. Burdett, G. Ritzinger, and Y. Lafon, Web services choreography description language version 1.0, w3c candidate recommendation, 2006.

J. Klingemann, J. Wasch, and K. Aberer, Deriving service models in cross-organizational workflows, Proceedings Ninth International Workshop on Research Issues on Data Engineering: Information Technology for Virtual Enterprises. RIDE-VE'99, pp.100-107, 1999.
DOI : 10.1109/RIDE.1999.758620

K. L. Ryan and . Ko, A computer scientist's introductory guide to business process management (bpm), Crossroads, vol.15, issue.4, 2009.

H. Kreger, Fulfilling the Web services promise, Communications of the ACM, vol.46, issue.6, p.29, 2003.
DOI : 10.1145/777313.777334

M. Last, Y. Klein, and A. Kandel, Knowledge discovery in time series databases, IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), vol.31, issue.1, pp.31-160, 2001.
DOI : 10.1109/3477.907576

N. Leavitt, Are Web services finally ready to deliver?, Computer, vol.37, issue.11, pp.14-18, 2004.
DOI : 10.1109/MC.2004.199

F. Leymann and D. Roller, Workflow-based applications, IBM Syst, J, vol.36, issue.1, pp.102-123, 1997.

C. Li, M. Reichert, and A. Wombacher, Discovering Reference Models by Mining Process Variants Using a Heuristic Approach, BPM '09: Proceedings of the 7th International Conference on Business Process Management, pp.344-362, 2009.
DOI : 10.1016/j.datak.2008.05.001

M. Lin and S. Lee, Fast discovery of sequential patterns through memory indexing and database partitioning, J. Inf. Sci. Eng, vol.21, issue.1, pp.109-128, 2005.

W. Lin, M. A. Orgun, and G. J. Williams, An overview of temporal data mining, 1st Australian data mining workshop (ADM02), pp.83-90, 2002.

K. Musaraj, T. Yoshida, and F. Daniel, Mohand-Said Hacid, Fabio Casati, and Boualem Benatallah, Message correlation and web service protocol mining from inaccurate logs, International Conference on Web Services (ICWS'10), pp.259-266, 2010.

R. M. Hamid and . Nezhad, Discovery and adaptation of process views, 2008.

R. Hamid, B. Motahari-nezhad, F. Benatallah, F. Casati, and . Toumani, Web services interoperability specifications, Computer, vol.39, pp.24-32, 2006.

R. Hamid, B. Motahari-nezhad, and . Benatallah, Régis Saint-Paul, Fabio Casati, and Periklis Andritsos, Process spaceship: discovering and exploring process views from event logs in data spaces, Very Large Data Bases, vol.1, issue.2, pp.1412-1415, 2008.

R. Hamid, R. Motahari-nezhad, B. Saint-paul, F. Benatallah, and . Casati, Protocol discovery from imperfect service interaction logs, pp.1405-1409, 2007.

C. France, &. , N. Usa, and . Sage-combinat, Extensible toolbox for computer exploration in algebraic combinatorics

. Tech, . Rep, and . Omg, Business process modeling notation (bpmn) specification, final adopted specification, Feb, 2006.

O. David and . Riordan, Business process standards for web services, 2002.

P. Papapetrou, G. Kollios, S. Sclaroff, and D. Gunopulos, Discovering Frequent Arrangements of Temporal Intervals, Fifth IEEE International Conference on Data Mining (ICDM'05), pp.354-361, 2005.
DOI : 10.1109/ICDM.2005.50

P. Michael, D. Papazoglou, and . Georgakopoulos, Introduction: Service oriented computing, Commun. ACM, vol.46, issue.10, pp.24-28, 2003.

G. Pass, A. Chowdhury, and C. Torgeson, A picture of search, Proceedings of the 1st international conference on Scalable information systems , InfoScale '06, 2006.
DOI : 10.1145/1146847.1146848

J. Pei, J. Han, B. Mortazavi-asl, J. Wang, H. Pinto et al., Mining sequential patterns by pattern-growth: The prefixspan approach, IEEE Transactions on Knowledge and Data Engineering, vol.16, issue.11, pp.1424-1440, 2004.

C. Peltz, Web services orchestration and choreography, Computer, vol.36, issue.10, pp.46-52, 2003.
DOI : 10.1109/MC.2003.1236471

R. Shankar, A. Ponnekanti, and . Fox, Interoperability among independently evolving web services, Proceedings of the 5th ACM/IFIP/USENIX international conference on Middleware, pp.331-351, 2004.

A. Pryke, The data mine, 2010.

A. J. Rembert, Comprehensive workflow mining, Proceedings of the 44th annual southeast regional conference on , ACM-SE 44, pp.222-227, 2006.
DOI : 10.1145/1185448.1185498

J. F. Roddick, K. Hornsby, and M. Spiliopoulou, An Updated Bibliography of Temporal, Spatial, and Spatio-temporal Data Mining Research, Proceedings of the 1st International Workshop on Temporal, Spatial, and Spatio-Temporal Data Mining-Revised Papers, pp.147-164, 2001.
DOI : 10.1007/3-540-45244-3_12

S. Ross, A first course in probability, pp.171-184, 2006.

A. Rozinat, M. P. Wil, and . Van-der-aalst, Conformance testing: Measuring the fit and appropriateness of event logs and process models, Business Process Management Workshops, pp.163-176, 2005.

L. Sacchi, C. Larizza, C. Combi, and R. Bellazzi, Data mining with Temporal Abstractions: learning rules from time series, Data Mining and Knowledge Discovery, vol.13, issue.6, pp.217-247, 2007.
DOI : 10.1007/s10618-007-0077-7

B. Serrour, D. P. Gasparotto, H. Kheddouci, and B. Benatallah, Message Correlation and Business Protocol Discovery in Service Interaction Logs, 20th International Conference on Advanced Information Systems Engineering (CAISE'08), pp.405-419, 2008.
DOI : 10.1007/978-3-540-69534-9_31
URL : https://hal.archives-ouvertes.fr/hal-00385436

G. Shafer, A mathematical theory of evidence, 1976.

R. Silva, J. Zhang, and J. G. Shanahan, Probabilistic workflow mining, Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining , KDD '05, pp.5-275, 2005.
DOI : 10.1145/1081870.1081903
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.71.9734

M. Sipser, Introduction to the Theory of Computation, ACM SIGACT News, vol.27, issue.1, 1997.
DOI : 10.1145/230514.571645

P. Smart, H. Maddern, and R. S. Maull, Understanding Business Process Management: Implications for Theory and Practice, British Journal of Management, vol.3, issue.4, pp.491-507, 2008.
DOI : 10.1111/j.1467-8551.2008.00594.x
URL : https://ore.exeter.ac.uk/repository/bitstream/10036/3448/9/0708.pdf

M. Stal, Web services: beyond component-based computing, Communications of the ACM, vol.45, issue.10, pp.71-76, 2002.
DOI : 10.1145/570907.570934

Z. Suraj, Discovering Concurrent Process Models in Data: A Rough Set Approach, Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC'09), pp.12-19, 2009.
DOI : 10.1007/978-3-642-10646-0_2

T. Kishor and . Trivedi, Probability and statistics with reliability, queueing and computer science applications, 2004.

A. K. Tung, H. Lu, J. Han, and L. Feng, Efficient mining of intertransaction association rules, Knowledge and Data Engineering, IEEE Transactions on, vol.15, issue.1, pp.43-56, 2003.

M. Turner, D. Budgen, and P. Brereton, Turning software into a service, Computer, vol.36, issue.10, pp.38-44, 2003.
DOI : 10.1109/MC.2003.1236470

M. P. Wil, A. H. Van-der-aalst, M. Ter-hofstede, and . Weske, Business process management: A survey, Business Process Management, pp.1-12, 2003.

M. P. Wil, K. Van-der-aalst, M. Van-hee, R. Hee, J. De-vries et al., Workflow management: Models, methods, and systems, 2002.

M. P. Wil, A. H. Van-der-aalst, M. Hofstede, and . Weske, Business process management: A survey, Proceedings of the 1st International Conference on Business Process Management, pp.1-12, 2003.

M. P. Wil, A. J. Van-der-aalst, L. Weijters, and . Maruster, Workflow mining: Discovering process models from event logs, IEEE Transactions on Knowledge and Data Engineering, vol.16, issue.9, pp.1128-1142, 2004.

R. Villafane, K. A. Hua, D. Tran, and B. Maulik, Knowledge discovery from series of interval events, Journal of Intelligent Information Systems, vol.15, issue.1, pp.71-89, 2000.
DOI : 10.1023/A:1008781812242

H. Barbara-von, Business rules applied: Building better systems using the business rules approach, 2001.

W. M. Wil, M. P. Van-der-aalst, B. F. Van-dongen, J. Herbst, L. Maruster et al., Workflow mining: a survey of issues and approaches, Data Knowl, pp.47-237, 2003.

E. Winarko and J. F. Roddick, Discovering Richer Temporal Association Rules from Interval-Based Data, Proceedings of the international conference on data warehousing and knowledge discovery DaWaK, pp.315-325, 2005.
DOI : 10.1007/11546849_31

L. Yingjiu, N. Peng, W. X. Sean, and J. Sushil, Discovering calendarbased temporal association rules, Data Knowl. Eng, vol.44, issue.2, pp.193-218, 2003.

J. M. Zaha, A. Barros, M. Dumas, and A. Ter-hofstede, Let's dance: A language for service behavior modeling, Cooperative Information Systems, International Conference -CoopIS '06, pp.145-162, 2006.

D. Zwillinger, Crc standard mathematical tables and formulae, affine transformations, 1995.
DOI : 10.1201/9781420035346