Abstract
In this chapter, we propose an analysis of the approaches and methods available for the automated extraction of knowledge from event flows. We specifically focus on the reconstruction of processes from automatically generated events logs. In this context, we consider that knowledge can be directly gathered by means of the reconstruction of business process models. In the ArtDECO project, we frame such approaches inside delta analysis, that is the detection of differences of the executed processes from the planned models. To this end, we provide an overview of the different techniques available for process reconstruction, and propose an approach for the detection of deviations. To show its effectiveness, we instantiate the usage to the ArtDECO case study.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Aires da Silva, G., Ferreira, D.R.: Applying Hidden Markov Models to Process Mining. In: Rocha, A., Restivo, F., Reis, L.P., Torrao, S. (eds.) Sistemas e Tecnologias de Informacao: Actas da 4a Conferencia Iberica de Sistemas e Tecnologias de Informacao, pp. 207–210. AISTI/FEUP/UPF (2009)
Coman, I., Sillitti, A.: An Empirical Exploratory Study on Inferring Developers’ Activities from Low-Level Data. In: 19th International Conference on Software Engineering and Knowledge Engineering (SEKE 2007), Boston, MA, USA, July 9-11 (2007)
Coman, I., Sillitti, A.: Automated Identification of Tasks in Development Sessions. In: 16th IEEE International Conference on Program Comprehension (ICPC 2008), Amsterdam, The Netherlands, June 10-13 (2008)
Coman, I., Sillitti, A., Succi, G.: Investigating the Usefulness of Pair-Programming in a Mature Agile Team. In: 9th International Conference on eXtreme Programming and Agile Processes in Software Engineering (XP 2008), Limerick, Ireland, June 10-14 (2008)
Coman, I., Sillitti, A.: Automated Segmentation of Development Sessions into Task-related Subsections. International Journal of Computers and Applications 31(3) (2009)
Coman, I., Sillitti, A., Succi, G.: A Case-study on Using an Automated In-process Software Engineering Measurement and Analysis System in an Industrial Environment. In: 31st International Conference on Software Engineering (ICSE 2009), Vancouver, BC, Canada, May 16-24 (2009)
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)
Ferreira, D., Zacarias, M., Malheiros, M., Ferreira, P.: Approaching Process Mining with Sequence Clustering: Experiments and Findings. In: Alonso, G., Dadam, P., Rosemann, M. (eds.) BPM 2007. LNCS, vol. 4714, pp. 360–374. Springer, Heidelberg (2007)
Fronza, I., Sillitti, A., Succi, G.: Modeling Spontaneous Pair Programming when New Developers Join a Team. In: 3rd International Symposium on Empirical Software Engineering and Measurement (ESEM 2009), Lake Buena Vista, FL, USA, October 15-16 (2009)
Greco, G., Guzzo, A., Pontieri, L., Sacca’, D.: Discovering expressive process models by clustering log traces. IEEE Trans. Knowl. Data Eng. 18(8), 1010–1027 (2006)
Greco, G., Guzzo, A., Pontieri, L.: Mining taxonomies of process models. Data & Knowledge Engineering 67(1), 74–102 (2008)
Goedertier, S., Martens, D., Baesens, B., Haesen, R., Vanthienen, J.: Process Mining as First-Order Classification Learning on Logs with Negative Events. In: ter Hofstede, A.H.M., Benatallah, B., Paik, H.-Y. (eds.) BPM Workshops 2007. LNCS, vol. 4928, pp. 42–53. Springer, Heidelberg (2008)
Guenther, C.W., Van der Aalst, W.M.P.: Mining Activity Clusters from Low-Level Event Logs. BETA Working Paper Series, WP 165. Eindhoven University of Technology, Eindhoven (2006)
Günther, C.W., van der Aalst, W.M.P.: Fuzzy Mining – Adaptive Process Simplification Based on Multi-perspective Metrics. In: Alonso, G., Dadam, P., Rosemann, M. (eds.) BPM 2007. LNCS, vol. 4714, pp. 328–343. Springer, Heidelberg (2007)
Günther, C.W., Rozinat, A., van der Aalst, W.M.P.: Activity Mining by Global Trace Segmentation. In: Rinderle-Ma, S., Sadiq, S., Leymann, F. (eds.) BPM 2009. LNBIP, vol. 43, pp. 128–139. Springer, Heidelberg (2010)
Herbst, J.: Dealing with concurrency in workflow induction. In: Proceedings of the 7th European Concurrent Engineering Conference, Society for Computer Simulation (SCS), pp. 169-174 (2000)
Herbst, J., Karagiannis, D.: Integrating Machine Learning and Workflow Management to Support Acquisition and Adaptation of Workflow Models. International Journal of Intelligent Systems in Accounting, Finance and Management 9, 67–92 (2000)
Janes, A., Scotto, M., Sillitti, A., Succi, G.: A perspective on non-invasive software management. In: 2006 IEEE Instrumentation and Measurement Technology Conference (IMTC 2006), Sorrento, Italy, April 24-27 (2006)
Janes, A., Sillitti, A., Succi, G.: Non-invasive software process data collection for expert identification. In: 20th International Conference on Software Engineering and Knowledge Engineering (SEKE 2008), San Francisco, CA, USA, July 1-3 (2008)
Lamma, E., Mello, P., Riguzzi, F., Storari, S.: Applying Inductive Logic Programming to Process Mining. In: Blockeel, H., Ramon, J., Shavlik, J., Tadepalli, P. (eds.) ILP 2007. LNCS (LNAI), vol. 4894, pp. 132–146. Springer, Heidelberg (2008)
Maruster, L., Weijters, A.J.M.M., Van der Aalst, W.M.P., Van den Bosch, A.: A rule-based approach for process discovery: Dealing with noise and imbalance in process logs. Data Mining and Knowledge Discovery 13(1), 67–87 (2006)
de Medeiros, A.K.A., Weijters, A.J.M.M., van der Aalst, W.M.P.: Genetic Process Mining: A Basic Approach and Its Challenges. In: Bussler, C.J., Haller, A. (eds.) BPM 2005. LNCS, vol. 3812, pp. 203–215. Springer, Heidelberg (2006)
de Medeiros, A.K.A., Guzzo, A., Greco, G., van der Aalst, W.M.P., Weijters, A.J.M.M., van Dongen, B.F., Saccà , D.: Process Mining Based on Clustering: A Quest for Precision. In: ter Hofstede, A.H.M., Benatallah, B., Paik, H.-Y. (eds.) BPM Workshops 2007. LNCS, vol. 4928, pp. 17–29. Springer, Heidelberg (2008)
Rozinat, A., van der Aalst, W.M.P.: Conformance Testing: Measuring the Fit and Appropriateness of Event Logs and Process Models. In: Bussler, C.J., Haller, A. (eds.) BPM 2005. LNCS, vol. 3812, pp. 163–176. Springer, Heidelberg (2006)
Schimm, G.: Mining exact models of concurrent workflows. Comput. Ind. 53, 265–281 (2004)
Scotto, M., Sillitti, A., Succi, G., Vernazza, T.: Dealing with Software Metrics Collection and Analysis: a Relational Approach. Studia Informatica Universalis, Suger 3(3), 343–366 (2004)
Sillitti, A., Janes, A., Succi, G., Vernazza, T.: Collecting, Integrating and Analyzing Software Metrics and Personal Software Process Data. In: Proceedings of the 29th EUROMICRO Conference (2003)
Van der Aalst, W.M.P., Weijters, A.: Process mining: a research agenda. Comput. Ind. 53, 231–244 (2002)
Van der Aalst, W.M.P., Van Dongen, B.F., Herbst, J., Maruster, L., Schimm, G., Weijters, A.J.M.M.: Workflow mining: A survey of issues and approaches. Data & Knowledge Engineering 47(2), 237–267 (2003)
Van der Aalst, W.M.P., Weijters, A.J.M.M., Maruster, L.: Workflow Mining: Discovering Process Models from Event Logs. IEEE Transactions on Knowledge and Data Engineering 16(9), 1128–1142 (2004)
Van der Aalst, W.M.P., Reijers, H., Song, M.: Discovering Social Networks from Event Logs. Computer Supported Cooperative work 14(6), 549–593 (2005)
van der Aalst, W.M.P., de Medeiros, A.K.A., Weijters, A.J.M.M.: Genetic Process Mining. In: Ciardo, G., Darondeau, P. (eds.) ICATPN 2005. LNCS, vol. 3536, pp. 48–69. Springer, Heidelberg (2005)
Song, M., Günther, C.W., van der Aalst, W.M.P.: Trace Clustering in Process Mining. In: Ardagna, D., Mecella, M., Yang, J. (eds.) BPM 2008 Workshops. LNBIP, vol. 17, pp. 109–120. Springer, Heidelberg (2009)
Weijters, A.J.M.M., Van der Aalst, W.M.P.: Rediscovering Workflow Models from Event-Based Data using Little Thumb. Integrated Computer-Aided Engineering 10(2), 151–162 (2003)
Wen, L., Wang, J., Van der Aalst, W.M.P., Wang, Z., Sun, J.: A Novel Approach for Process Mining Based on Event Types. BETA Working Paper Series, WP 118. Eindhoven University of Technology, Eindhoven (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Mahdiraji, A.R., Rossi, B., Sillitti, A., Succi, G. (2012). Knowledge Extraction from Events Flows. In: Anastasi, G., Bellini, E., Di Nitto, E., Ghezzi, C., Tanca, L., Zimeo, E. (eds) Methodologies and Technologies for Networked Enterprises. Lecture Notes in Computer Science, vol 7200. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31739-2_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-31739-2_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31738-5
Online ISBN: 978-3-642-31739-2
eBook Packages: Computer ScienceComputer Science (R0)