Abstract
Business process management (BPM) continues to play a significant role in today’s highly globalized world. In order to detect and prevent the gap between reference process model and the actual operation, process mining techniques discover operational model on the basis of the process logs. An important issue at BPM is to measure the similarity between the reference process model and discovered process model so that it can be possible to pinpoint where process participants deviate from the intended process description. In this paper, a hybrid quantitative approach is presented to measure the similarity between the process models. The proposed similarity metric is based on a hybrid process mining technique that makes use of genetic algorithms. The proposed approach itself is also a hybrid model that considers process activity dependencies and process structure.
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References
van den Aalst, W.M.P., Gunther, C., Recker, J., Reichert, M.: Using Process Mining to Analyze and Improve Process Flexibility. In: 7th Workshop on BPMDS 2006, CAiSE 2006 Workshop (2006)
Măruşter, L., Weijters, A.J.M.M.T., van der Aalst, W.M.P., van den Bosch, A.: Process Mining: Discovering Direct Successors in Process Logs. In: Lange, S., Satoh, K., Smith, C.H. (eds.) DS 2002. LNCS, vol. 2534, pp. 364–373. Springer, Heidelberg (2002)
Weijters, A., van den Aalst, W.M.P.: Process Mining Discovering Workflow Models from Event-Based Data. In: Proc. of the 13th Belgium-Netherlands Conference on Artificial Intelligence, pp. 283–290 (2001)
van den Aalst, W.M.P., Dongen, B.F., Herbst, J.L.M., Schimm, G., Weijters, T.A.J.M.M.: Workflow Mining: A Survey of Issues and Approaches. Data & Knowledge Engineering 47(2), 237–267 (2003)
Gunther, C.W., van den Aalst, W.M.P.: Process Mining in Case Handling Systems. In: Proc. PRIMIUM Subconference at the Multikonferenz Wirtschaftsinformatik (2006)
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. 469–483. 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 7(3), 215–249 (1998)
Weijters, A.J.M.M., van den Aalst, W.M.P.: Rediscovering Workflow Models from Event-Based Data Using Little Thumb. Integrated Computer-Aided Engineering 10(2), 151–162 (2003)
van den Aalst, W.M.P., Weijters, A.J.M.M., Maruster, L.: Workflow Mining: Discovering Process Models from Event Logs. Transaction on Knowledge and Data Engineering 16(9), 1128–1142 (2004)
van den Aalst, W.M.P., Dongen, B.F., Herbst, J.L.M., Schimm, G., Weijters, T.A.J.M.M.: Workflow Mining: A Survey of Issues and Approaches. Data & Knowledge Engineering 47(2), 237–267 (2003)
van den Aalst, W.M.P.: Business Alignment: Using Process Mining as a Tool for Delta Analysis and Conformance Testing. Requirements Engineering 10(3), 198–211 (2005)
Esgin, E., Senkul, P., Cimenbicer, C.: A Hybrid Approach for Process Mining: Using From-to Chart Arranged by Genetic Algorithms. In: Graña Romay, M., Corchado, E., Garcia Sebastian, M.T. (eds.) HAIS 2010. LNCS, vol. 6076, pp. 178–186. Springer, Heidelberg (2010)
Kleiner, N.: Delta Analysis with Workflow Logs: Aligning Business Process Prescriptions and Their Reality. Requirements Engineering 10(3), 212–222 (2005)
van Dongen, B.F., Dijkman, R., Mendling, J.: Measuring Similarity between Business Process Models. In: Bellahsène, Z., Léonard, M. (eds.) CAiSE 2008. LNCS, vol. 5074, pp. 450–464. Springer, Heidelberg (2008)
Nejati, S., Sabetzadeh, M., Chechik, M., Easterbrook, S., Zave, P.: Matching and merging of statecharts specifications. In: Proc. of 29th ICSE, pp. 54–63. IEEE Computer Society, Los Alamitos (2007)
Bunke, H., Shearer, K.: A Graph Distance Metric Based on the Maximal Common Subgraph. Pattern Recognition Letters 19(3), 255–259 (1998)
Zhang, K., Shasha, D.: Simple Fast Algorithms for the Editing Distance between Trees and Related Problems. SIAM Journal of Computing 18(6), 1245–1262 (1989)
Huang, K., Zhou, Z., Han, Y., Li, G., Wang, J.: An Algorithm for Calculating Process Similarity to Cluster Open-Source Process Designs. In: Proc. of 4th Grid and Cooperative Computing, vol. 3252, pp. 107–114 (2004)
Esgin, E., Senkul, P.: Hybrid Approach to Process Mining: Finding Immediate Successors of a Process by Using From-to Chart. In: Int. Conf. on Machine Learning and Applications, pp. 664–668. IEEE Computer Society, Los Alamitos (2009)
Francis, R.L., McGinnis, L.F., White, J.A.: Facility Layout and Location: An Analytical Approach. Prentice Hall, New Jersey (1992)
Bae, J., Liu, L., Caverlee, J., Zhang, L., Bae, Z.: Process Mining and Integration using Distance Measures. International Journal of Web Services Research 1(4), 14–32 (2006)
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Esgin, E., Senkul, P. (2011). Delta Analysis: A Hybrid Quantitative Approach for Measuring Discrepancies between Business Process Models. In: Corchado, E., Kurzyński, M., Woźniak, M. (eds) Hybrid Artificial Intelligent Systems. HAIS 2011. Lecture Notes in Computer Science(), vol 6678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21219-2_38
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DOI: https://doi.org/10.1007/978-3-642-21219-2_38
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