Abstract
Engineering workflow applications are becoming more and more complex, involving numerous interacting business objects within considerable processes. Analysing the interaction structure of those complex applications will enable them to be well understood, controlled, and redesigned. Our contribution to workflow mining is a statistical technique to discover workflow patterns from event-based log. Our approach is characterised by a ”local” workflow patterns discovery that allows to cover partial results through a dynamic programming algorithm. Those local discovered workflow patterns are then composed iteratively until discovering the global workflow model. Our approach has been implemented within our prototype WorkflowMiner.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Van Der Aalst, W.M.P., Ter Hofstede, A.H.M., Kiepuszewski, B., Barros, A.P.: Workflow patterns. Distrib. Parallel Databases 14(1), 5–51 (2003)
Cook, J.E., Wolf, A.L.: Event-based detection of concurrency. In: 6th ACM SIGSOFT international symposium on Foundations of software engineering. ACM Press, New York (1998)
Gaaloul, W., Bhiri, S., Godart, C.: Discovering workflow transactional behaviour event-based log. In: 12th International Conference on Cooperative Information Systems (CoopIS 2004), Larnaca, Cypru, October 25-29. LNCS. Springer, Heidelberg (2004)
Gaaloul, W., Godart, C.: Mining Workflow Recovery from Event Based Logs. In: van der Aalst, W.M.P., Benatallah, B., Casati, F., Curbera, F. (eds.) BPM 2005. LNCS, vol. 3649, pp. 169–185. Springer, Heidelberg (2005)
Baïna, K., Berrada, I., Kjiri, L.: A Balanced Scoreboard Experiment for Business Process Performance Monitoring: Case study. In: 1st International E-Business Conference (IEBC 2005), Tunis, Tunisia, June 24-25 (2005)
van der Aalst, W.M.P.: Business alignment: Using process mining as a tool for delta analysis. In: CAiSE Workshops (2), pp. 138–145 (2004)
Benatallah, B., Casati, F., Toumani, F.: Analysis and Management of Web Service Protocols. In: Atzeni, P., Chu, W., Lu, H., Zhou, S., Ling, T.-W. (eds.) ER 2004. LNCS, vol. 3288, pp. 524–541. Springer, Heidelberg (2004)
Baïna, K., Benatallah, B., Casati, F., Toumani, F.: Model-Driven Web Service Development. In: Persson, A., Stirna, J. (eds.) CAiSE 2004. LNCS, vol. 3084, pp. 290–306. Springer, Heidelberg (2004)
Agrawal, R., Gunopulos, D., Leymann, F.: Mining Process Models from Workflow Logs. In: Schek, H.-J., Saltor, F., Ramos, I., Alonso, G. (eds.) EDBT 1998. LNCS, vol. 1377, pp. 469–498. Springer, Heidelberg (1998)
Cook, J.E., Wolf, A.L.: Discovering models of software processes from event-based data. ACM Transactions on Software Engineering and Methodology (TOSEM) 7(3), 215–249 (1998)
Cook, J.E., Wolf, A.L.: Event-based detection of concurrency. In: Proceedings of the 6th ACM SIGSOFT international symposium on Foundations of software engineering, pp. 35–45. ACM Press, New York (1998)
Herbst, J.: A Machine Learning Approach to Workflow Management. In: Lopez de Mantaras, R., Plaza, E. (eds.) ECML 2000. LNCS (LNAI), vol. 1810, pp. 183–194. Springer, Heidelberg (2000)
Herbst, J., Karagiannis, D.: Integrating machine learning and workflow management to support acquisition and adaptation of workflow models. In: 9th International Workshop on DEXA, p. 745. IEEE Computer Society Press, Los Alamitos (1998)
Sayal, M., Casati, F., Shan, M.C., Dayal, U.: Business process cockpit. In: Proceedings of 28th International Conference on Very Large Data Bases (VLDB 2002), pp. 880–883 (2002)
Grigori, D., Casati, F., Castellanos, M., Dayal, U., Sayal, M., Shan, M.-C.: Business process intelligence. Comput. Ind. 53(3), 321–343 (2004)
Gaaloul, W., Baïna, K., Godart, C.: Towards Mining Structural Workflow Patterns. In: Andersen, K.V., Debenham, J., Wagner, R. (eds.) DEXA 2005. LNCS, vol. 3588, pp. 24–33. Springer, Heidelberg (2005)
van der Aalst, W.M.P., van Dongen, B.F.: Discovering workflow performance models from timed logs. In: 1st International Conference on Engineering and Deployment of Cooperative Information Systems, pp. 45–63. Springer, Heidelberg (2002)
Weijters, A.J.M.M., van der Aalst, W.M.P.: Workflow mining: Discovering workflow models from event-based data. In: ECAI Workshop on Knowledge Discovery and Spatial Data, pp. 78–84 (2002)
Herbst, J., Karagiannis, D.: Workflow mining with inwolve. Comput. Ind. 53(3), 245–264 (2004)
Schimm, G.: Process Miner - A Tool for Mining Process Schemes from Event-Based Data. In: European Conference on Logics in AI, pp. 525–528. Springer, Heidelberg (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Gaaloul, W., Baïna, K., Godart, C. (2006). A Bottom-Up Workflow Mining Approach for Workflow Applications Analysis. In: Lee, J., Shim, J., Lee, Sg., Bussler, C., Shim, S. (eds) Data Engineering Issues in E-Commerce and Services. DEECS 2006. Lecture Notes in Computer Science, vol 4055. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11780397_15
Download citation
DOI: https://doi.org/10.1007/11780397_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35440-6
Online ISBN: 978-3-540-35441-3
eBook Packages: Computer ScienceComputer Science (R0)