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Journal of Computer Science and Technology

, Volume 21, Issue 1, pp 66–71 | Cite as

A Workflow Process Mining Algorithm Based on Synchro-Net

  • Xing-Qi HuangEmail author
  • Li-Fu Wang
  • Wen Zhao
  • Shi-Kun Zhang
  • Chong-Yi Yuan
Article

Abstract

Sometimes historic information about workflow execution is needed to analyze business processes. Process mining aims at extracting information from event logs for capturing a business process in execution. In this paper a process mining algorithm is proposed based on Synchro-Net which is a synchronization-based model of workflow logic and workflow semantics. With this mining algorithm based on the model, problems such as invisible tasks and short-loops can be dealt with at ease. A process mining example is presented to illustrate the algorithm, and the evaluation is also given.

Keywords

workflow process mining workflow logic workflow semantics Petri net 

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References

  1. 1.
    Gianluigi Greco, Antonella Guzzo, Giuseppe Manco, Domenico Saccà. Mining, reasoning on workflows. IEEE Trans. Knowledge and Data Engineering, April 2005, 17(4): 519–534.Google Scholar
  2. 2.
    Wil van der Aalst, Kees Max van Hee. Workflow Management: Models, Methods and Systems. Cambridge, Massachusetts, London: The MIT Press, 2002, pp.22–73.Google Scholar
  3. 3.
    A K A de Medeiros, W M P van der Aalst, A J M M Weijters. Workflow Mining: Current Status and Future Directions. Meersman R et al. (eds.), CoopIS/DOA/ODBASE 2003, LNCS 2888, Berlin, Heidelberg: Springer-Verlag, 2003, pp.389–406.Google Scholar
  4. 4.
    W M P van der Aalst, A J M M Weijters, L Maruster. Workflow mining: Discovering process models from event logs. IEEE Trans. Knowledge and Data Engineering, September 2004, 16(9): 1128–1142.Google Scholar
  5. 5.
    Laura Maruster, A J M M (Ton) Weijters, W M P van der Aalst, Antal van den Bosch. Process mining: Discovering direct successors in process logs. Computers in Industry, April 2004, 53(3): 231–244.Google Scholar
  6. 6.
    A J M M Weijters, W M P van der Aalst. Rediscovering workflow models from event-based data using little thumb. Integrated Computer-Aided Engineering, 2001, 10(2): 151–162.Google Scholar
  7. 7.
    A K A de Medeiros, B F van Dongen, W M P van der Aalst, A J M M Weijters. Process mining: Extending the α-algorithm to mine short loops. BETA Working Paper Series, WP 113, Eindhoven University of Technology, Eindhoven, 2004.Google Scholar
  8. 8.
    Lijie Wen, Jianmin Wang, Wil M P van der Aalst, Zhe Wang, Jiaguang Sun. A novel approach for process mining based on event types. Tsinghua University and Eindhoven University of Technology, ISBN 90-386-2057-8/ISSN 1386-9213, WP 118, May 2004.Google Scholar
  9. 9.
    Gianluigi Greco, Antonella Guzzo, Giuseppe Manco, Domenico Saccà. Mining frequent instances on workflow. Workshop on ID&CBM, Hinterzarten, Germany, March 12, 2004, pp.209–221.Google Scholar
  10. 10.
    Gianluigi Greco, Antonella Guzzo, Giuseppe Manco, Domenico Saccà. On the mining of complex workflow schemas. In Proc. Italian Conference on Advanced Database Systems — SEBD04. S. Margherita di Pula (CA), Italy, 2004, pp.118–129.Google Scholar
  11. 11.
    Chongyi Yuan. Principals and Application of Petri Nets. Publishing House of Electronics Industry, 2005, pp.213–258.Google Scholar

Copyright information

© Springer Science + Business Media, Inc. 2006

Authors and Affiliations

  • Xing-Qi Huang
    • 1
    Email author
  • Li-Fu Wang
    • 1
  • Wen Zhao
    • 1
  • Shi-Kun Zhang
    • 1
  • Chong-Yi Yuan
    • 1
  1. 1.School of Electronics Engineering and Computer SciencePeking UniversityBeijingP.R. China

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