Extending the α-Algorithm to Mine Repetitive Task Based on Complex Structure

Abstract:

Process mining is helpful for deploying new business processes as well as auditing, analyzing and improving the already enacted ones. The business process system log often has a large number of the namesake task and repetitive task. The existing alpha algorithm of the mining algorithm cannot distinguish them very well. It leads to the results that the process mining often produce inaccurate flow model. In order to improve the accuracy of the process mining, the paper puts forward an improved method. The new method not only can dig the complex structure, such as circulation structure, free choice structure and so on, it still can dig the eponymous task and repeat task in the log.

• Periodical: Advanced Materials Research (Volumes 989-994)
• Pages: 1918-1923
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.989-994.1918
• Online since: July 2014
• Authors: Hong Li, Yu Wei*, Xiao Hu Ye, Shao Wen Yao, Jun Yang
• Keywords: Complex Structure, Namesake Task, Process Mining, Repetitive Task

References

[1] J.E. Cook and A.L. Wolf. Automating process discovery through event-data analysis. In Proceedings of the 17th international conference on Software engineering, pages 73-82. ACM, New York, NY, USA, (1995).

DOI: 10.1145/225014.225021

[2] J.E. Cook and A.L. Wolf. Discovering Models of Software Processes from Event-Based Data. ACM Transactions on Software Engineering and Methodology, 7(3): 215-249, (1998).

DOI: 10.1145/287000.287001

[3] YE Xiaohu, YAO Shaowen, LIU Fangyu, XUE Gang. Towards Improving Process Mining Results Base on Invisible Tasks. ACMSIC2011 B0406155.

[4] Van der Aalst W M P, Weijters A J M M. Process mining—a research agenda, computers in industry [J]. 2004, 53(3): 231-244.

DOI: 10.1016/j.compind.2003.10.001

[5] Agrawal R, Gunopulos D, Leymann E Mining process models from workflow log [C]. Proceedings of the 6th International Conference on Extending Database Technology, USA, 1998: 469-483.

DOI: 10.1007/bfb0101003

[6] Herbst J, Dealing with concurrency in workflow induction[C]. Proceedings in the 7 European Concurrent Engineering Conference, SCS Europe, (2000).

[7] Joachim H, Dimitris Karagiannis. Workflow mining with InWoLvE [J]. Computers in Industry, 2004, 53(4): 245—264.

DOI: 10.1016/j.compind.2003.10.002

[8] Guido Schimm. Mining exact models of concurrent workflows [J]. Computers in Industry, 2004, 53(2): 265—281.

DOI: 10.1016/j.compind.2003.10.003

[9] AALST W M P, WEIJTERS T, MARUSTER I. Workflow mining: discovering process models from event logs [J]. IEEE Transactions on Knowledge and Data Engineering, 2004, 1 6(9): 1128-1142.

DOI: 10.1109/tkde.2004.47

[10] Van der Aalst W M P, Weijters A J M M, Marudter L. Workflow mining: which processes Can be Rediscovered [C]. IEEE Transactions on Knowledge and Data Engineering, Eindhoven, 2002: 67-91.

[11] Van der Aalst W M P, Van Dongen B, E. Discovering workflow performance models from timed logs [C]. International Conference on Engineering and Deployment of Cooperative Inform action System, Berlin, 2002: 45-63.

DOI: 10.1007/3-540-45785-2_4

[12] Chinces, D. Business process mining algorithms. IEEE International Conference on Intelligent Computer Communication and Processing (ICCP). 2013, 9: 271-277.

DOI: 10.1109/iccp.2013.6646120

[13] Weber, P. A Framework for the Analysis of Process Mining Algorithms. Systems, Man, and Cybernetics: Systems, IEEE Transactions on (Volume: 43, Issue: 2). 2013, 3: 303 – 317.

DOI: 10.1109/tsmca.2012.2195169