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Agent Assignment for Process Management: Pattern Based Agent Performance Evaluation

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Agents and Data Mining Interaction (ADMI 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5680))

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Abstract

In almost all workflow management system the role concept is determined once at the introduction of workflow application and is not reevaluated to observe how successfully certain processes are performed by the authorized agents. This paper describes an approach which evaluates how agents are working successfully and feed this information back for future agent assignment to achieve maximum business benefit for the enterprise. The approach is called Pattern based Agent Performance Evaluation (PAPE) and is based on machine learning technique combined with post processing technique. We report on the result of our experiments and discuss issues and improvement of our approach.

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References

  1. Rozinat, A., van der Aalst, W.M.P.: Decision Mining in Business Processes. Developmental Review (2006), http://prom.win.tue.nl/research/wiki/publications/beta_164 BPM Center Report BPM-06-10, BPMcenter.org

  2. Bussler, C.: Organisationsverwaltung in Workflow-Management-Systemen (in German). Deutscher Universitäts-Verlag (1998)

    Google Scholar 

  3. Cao, L., Zhang, C., Yu, P., et al.: Domain-Driven actionable knowledge discovery. IEEE Intelligent Systems 22(4), 78–89 (2007)

    Article  Google Scholar 

  4. Witten, I.H., Frank, E.: Data Mining: Practical Machine Learning Tools and Techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)

    MATH  Google Scholar 

  5. Jablonski, S., Bussler, C.: Workflow Management: Modeling Concepts, Architecture and Implementation. International Thomson Computer Press (1996)

    Google Scholar 

  6. Yingbo, L., Jianmin, W., Jiaguang, S.: A Machine Learning Approach to Semi-Automating Workflow Staff Assignment. In: SAC 2007, Seol, Korea (2007)

    Google Scholar 

  7. Ly, L., Rinderle, S., Dadam, P., Reichert, M.: Mining Staff Assignment Rules from Event-Based Data. In: Bussler, C.J., Haller, A. (eds.) BPM 2005. LNCS, vol. 3812, pp. 177–190. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  8. Song, M., von der Aalst, W.M.P.: Towards Comprehensive Support for Organizational Mining, BETA Working Paper Series, WP 211, Eindhoven University of Technology

    Google Scholar 

  9. Moore, C.: Common Mistakes in Workflow Implementations. Giga Information Group, Cambridge (2002)

    Google Scholar 

  10. Bannerman, P.L.: Capturing Business Benefits from Process Improvement: Four Fallacies and What to Do About Them. In: BIPI 2008, Leipzig, Germany (2008)

    Google Scholar 

  11. Quinlan, R.: C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo (1993)

    Google Scholar 

  12. Rinderle-Ma, S., van der Aalst, W.M.P.: Life-Cycle Support for Staff Assignment Rules in Process-Aware Information Systems. BETA Working Paper Series, WP 213, Eindhoven University of Technology, Eindhoven (2007), http://wwwis.win.tue.nl/%7Ewvdaalst/publications/p367.pdf

  13. 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)

    Chapter  Google Scholar 

  14. 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)

    Chapter  Google Scholar 

  15. van der Aalst, W.M.P.: Business Alignment: Using Process Mining as a Tool for Delta Analysis. In: Grundspenkis, J., Kirikova, M. (eds.) Proceedings of the 5th Workshop on Business Process Modeling, Development and Support (BPMDS 2004). Caise 2004 Workshops, vol. 2, pp. 138–145. Riga Technical University, Latvia (2004)

    Google Scholar 

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Jablonski, S., Talib, R. (2009). Agent Assignment for Process Management: Pattern Based Agent Performance Evaluation. In: Cao, L., Gorodetsky, V., Liu, J., Weiss, G., Yu, P.S. (eds) Agents and Data Mining Interaction. ADMI 2009. Lecture Notes in Computer Science(), vol 5680. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03603-3_12

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  • DOI: https://doi.org/10.1007/978-3-642-03603-3_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03602-6

  • Online ISBN: 978-3-642-03603-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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