Abstract
Ubiquitous Mobile Systems (UMSs) allow for automated capturing of events. Both mobility and ubiquity are supported by electronic means such as mobile phones and PDAs and technologies such as RFID, Bluetooth, WLAN, etc. These can be used to automatically record human behavior and business processes in detail. UMSs typically also allow for more flexibility. The combination of flexibility (i.e., the ability to deviate from standard procedures) and the automated capturing of events, provides an interesting application domain for process mining. The goal of process mining is to discover process models from event logs. The α-algorithm is a process mining algorithm whose application is not limited to ubiquitous and/or mobile systems. Unfortunately, the α-algorithm is unable to tackle so-called “short loops”, i.e., the repeated occurrence of the same event. Therefore, a new algorithm is proposed to deal with short loops: the α + -algorithm. This algorithm has been implemented in the EMiT tool.
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.
References
van der Aalst, W.M.P.: The Application of Petri Nets to Workflow Management. The Journal of Circuits, Systems and Computers 8(1), 21–66 (1998)
van der Aalst, W.M.P., van Dongen, B.F.: Discovering Workflow Performance Models from Timed Logs. In: Han, Y., Tai, S., Wikarski, D. (eds.) EDCIS 2002. LNCS, vol. 2480, pp. 45–63. Springer, Heidelberg (2002)
van der Aalst, W.M.P., van Hee, K.M.: Workflow Management: Models, Methods, and Systems. MIT press, Cambridge (2002)
van der Aalst, W.M.P., Song, M.: Mining Social Networks: Uncovering interaction patterns in business processes. In: Desel, J., Pernici, B., Weske, M. (eds.) BPM 2004. LNCS, vol. 3080, pp. 244–260. Springer, Heidelberg (2004)
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 and Knowledge Engineering 47(2), 237–267 (2003)
van der Aalst, W.M.P., Weijters, A.J.M.M. (eds.): Process Mining, Special Issue of Computers in Industry, vol. 53(3). Elsevier Science Publishers, Amsterdam (2004)
van der Aalst, W.M.P., Weijters, A.J.M.M., Maruster, L.: Workflow Mining: Discovering Process Models from Event Logs. QUT Technical report, FIT-TR-2003-03, Queensland University of Technology, Brisbane (2003) (Accepted for publication in IEEE Transactions on Knowledge and Data Engineering)
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)
Dustdar, S., Gall, H., Schmidt, R.: Web Services For Groupware in Distributed and Mobile Collaboration. In: Cremonesi, P. (ed.) Proceeding of the 12th IEEE Euromicro Conference on Parallel, Distributed and Network based Processing (PDP 2004), pp. 241–247. IEEE Computer Society, Los Alamitos (2004)
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)
IDS Scheer. ARIS Process Performance Manager (ARIS PPM) (2002), http://www.ids-scheer.com
de Medeiros, A.K.A., van der Aalst, W.M.P., Weijters, A.J.M.M.: Workflow Mining: Current Status and Future Directions. In: Meersman, R., Tari, Z., Schmidt, D.C. (eds.) CoopIS 2003, DOA 2003, and ODBASE 2003. LNCS, vol. 2888, pp. 389–406. Springer, Heidelberg (2003)
de Medeiros, A.K.A., van Dongen, B.F., van der Aalst, W.M.P., Weijters, A.J.M.M.: Process Mining: Extending the α-algorithm to Mine Short Loops. BETA Working Paper Series, WP 113, Eindhoven University of Technology, Eindhoven (2004)
zur Mühlen, M., Rosemann, M.: Workflow-based Process Monitoring and Controlling - Technical and Organizational Issues. In: Sprague, R. (ed.) Proceedings of the 33rd Hawaii International Conference on System Science (HICSS-33), pp. 1–10. IEEE Computer Society Press, Los Alamitos (2000)
Reisig, W., Rozenberg, G. (eds.): Lectures on Petri Nets I: Basic Models. LNCS, vol. 1491. Springer, Berlin (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. Morgan Kaufmann, San Francisco (2002)
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)
Weiser, M.: The computer for the 21st century. Scientific American 265(3), 94–104 (1991)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
de Medeiros, A.K.A., van Dongen, B.F., van der Aalst, W.M.P., Weijters, A.J.M.M. (2004). Process Mining for Ubiquitous Mobile Systems: An Overview and a Concrete Algorithm. In: Baresi, L., Dustdar, S., Gall, H.C., Matera, M. (eds) Ubiquitous Mobile Information and Collaboration Systems. UMICS 2004. Lecture Notes in Computer Science, vol 3272. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30188-2_12
Download citation
DOI: https://doi.org/10.1007/978-3-540-30188-2_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24100-3
Online ISBN: 978-3-540-30188-2
eBook Packages: Computer ScienceComputer Science (R0)