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Process Mining for Job Nets in Integrated Enterprise Systems

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 73))

Abstract

Batch jobs such as shell scripts are used to process large amounts of data in large scale enterprise systems. They are cascaded via certain signals or files to process their data in the proper order. Such cascaded jobs are called “job nets”. In many cases, it is difficult to understand the execution order of batch jobs in a job net because of the complexity of their relationships or because of lack of information. However, without understanding the behavior of batch jobs, we cannot achieve reliable system management. In this paper, we propose a method to derive the execution pattern of the job net from its execution logs. We developed a process mining method which takes into account the concurrency of batch job executions in large scale systems, and evaluated its accuracy by a conformance check method using job net logs obtained from an actual large scale supply chain management system.

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References

  1. Fujitsu SystemWalker Operation Manager v13.3, http://www.fujitsu.com/global/services/software/systemwalker/products/operationmgr/

  2. van der Aalst, W.M.P., Reijers, H.A., Weijters, A.J.M.M., van Dongen, B.F., Alves de Medeiros, A.K., Song, M., Verbeek, H.M.W.: Business Process Mining: An Industrial Application. Information Systems 32(5), 713–732 (2007)

    Article  Google Scholar 

  3. 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) (2004)

    Google Scholar 

  4. van der Aalst, W.M.P., Alves de Medeiros, A.K., 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)

    Chapter  Google Scholar 

  5. Weijters, A.J.M.M., van der Aalst, W.M.P., Alves de Medeiros, A.K.: Process Mining with the Heuristics Miner-algorithm. In: BETA Working Paper Series, WP 166, Eindhoven University of Technology (2006)

    Google Scholar 

  6. Rozinat, A., van der Aalst, W.M.P.: Conformance Checking of Processes Based on Monitoring Real Behavior. Information Systems 33(1), 64–95 (2008)

    Article  Google Scholar 

  7. Rozinat, A., van der Aalst, W.M.P.: Conformance Testing: Measuring the Fit and Appropriateness of Event Logs and Process Models. In: Proceedings of First International Workshop on Business Process Intelligence (BPI 2005), pp. 1–12 (2005)

    Google Scholar 

  8. Gansner, E., North, S.: In: An open graph visualization system and its applications to software engineering. Software – Practice & Experience 30(11), 1203–1233 (2000)

    Article  Google Scholar 

  9. Adobe Flex Framework, http://labs.adobe.com/technologies/flex/

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© 2011 Springer-Verlag Berlin Heidelberg

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Kikuchi, S., Matsumoto, Y., Adachi, M., Moritomo, S. (2011). Process Mining for Job Nets in Integrated Enterprise Systems. In: Filipe, J., Cordeiro, J. (eds) Enterprise Information Systems. ICEIS 2010. Lecture Notes in Business Information Processing, vol 73. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19802-1_21

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  • DOI: https://doi.org/10.1007/978-3-642-19802-1_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19801-4

  • Online ISBN: 978-3-642-19802-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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