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An experimental mining and analytics for discovering proportional process patterns from workflow enactment event logs

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Abstract

In this paper, we carry out an experimental analytics to show how much perfectly the conceptual mining framework is operable on re-discovering workflow process patterns and their enacted proportions from the workflow enactment event histories logged in a format of XES standardized schema. In principle, the framework must be able to properly handle all the workflow process patterns based upon the four types of control-flow primitives such as linear (sequential), disjunctive (selective), conjunctive (parallel), and loop (iterative) process patterns. The paper focuses on implementing an algorithmic mining framework only for discovering all the process patterns and their enacted proportions. To prove the functional correctness of the framework, we carry out an experimental mining and analytics on the real workflow instance enactment event histories of 10,000 workcases, and we finally visualize the mining and analytic artifacts and describe the implications of the results of the experiment.

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Notes

  1. The authors’ research group has been developing the overall functionality of the workflow mining and analytical framework. Now, we have already implemented the core algorithms and applied them to obtain the experimental analytics results described in this paper.

  2. Note that we assume the proportion of each out-going arc implies the proportional occurrence of the corresponding arc to be discovered from the workflow logs.

  3. XWELL stands for XML-based workflow execution logging mechanism and language.

  4. BPAF stands for business process audit format, which is supported by the Workflow Management Coalition (WfMC).

  5. XES stands for extensible event stream, which is supported by the extensible event stream working group of the IEEE standard committee.

References

  1. Casati, F., et al. (2002). Business process intelligence. Technical Report, HPL-2002-119, HP Laboratories Palo Alto.

  2. Grigori, D., Casati, F., Castellanos, M., Dayal, U., Sayal, M., & Shan, M.-C. (2004). Business process intelligence. Journal of Computers in Industry, 53(3), 321–343.

    Article  Google Scholar 

  3. van der Aalst, W. M. P., van Dongena, B. F., Herbst, J., Marustera, L., Schimm, G., & Weijters, A. J. M. M. (2003). Workflow mining: A survey of issues and approaches. Journal of Data & Knowledge Engineering, 47(2), 237–267.

    Article  Google Scholar 

  4. Kim, K., Yeon, M., Jeong, B., & Kim, K. (2017). A conceptual approach for discovering proportions of disjunctive routing patterns in a business process model. KSII Transactions on Internet and Information Systems, 11(2), 1148–1161.

    Google Scholar 

  5. Park, M., & Kim, K. (2008). Control-path oriented workflow intelligence analyses. Journal of Information Science and Engineering, 24, 343–359.

    Google Scholar 

  6. Kim, K. H. (2005). Control-path oriented workflow intelligence analysis on enterprize workflow grids. In Proceedings of the international conference on semantics, knowledge, and grid, Beijing, China.

  7. Kim, K. H., & Ellis, C. A. (2006). Workflow reduction for reachable-path rediscovery in workflow mining. In T. Y. Lin, S. Ohsuga, C.-J. Liau, & X. Hu (Eds.), Series of studies in computational intelligence: The foundations and novel approaches in data mining (Vol. 9, pp. 289–310). Springer.

  8. BPI Challenge 2012, 2013, 2014, 2015, 2016, 2017, 2018, 4TU. Centre for Research Data. https://data.4tu.nl/repository/collection:event-logs-real.

  9. IEEE. (2016). IEEE Standard for eXtensible Event Stream (XES) for achieving interoperability in event logs and event streams. In IEEE 1849–2016. https://doi.org/10.1109/IEEESTD.2016.7740858.

  10. Park, M., & Kim, K. (2007). XWELL: A XML-based workflow event logging mechanism and language for workflow mining systems. Lecture Notes in Computer Science, 4707, 900–909.

    Article  Google Scholar 

  11. zur Muehlen, M., & Swenson, K. D. (2011). BPAF: A standard for the interchange of process analytics data. Lecture Notes in Business Information Processing, 66, 170–181.

    Article  Google Scholar 

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Acknowledgements

This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education (Grant No. 2017R1A2B2010697).

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Authors and Affiliations

  1. Department of Computer Engineering, Kyunghee University, Yongin-si, Gyeonggi-do, 17104, Republic of Korea

    Kyoungsook Kim & Young-Koo Lee

  2. Division of Computer Science and Engineering, Kyonggi University, Suwon-si, Gyeonggi-do, 16227, Republic of Korea

    Hyun Ahn & Kwanghoon Pio Kim

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  1. Kyoungsook Kim
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  2. Young-Koo Lee
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  3. Hyun Ahn
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  4. Kwanghoon Pio Kim
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Correspondence to Kwanghoon Pio Kim.

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Kim, K., Lee, YK., Ahn, H. et al. An experimental mining and analytics for discovering proportional process patterns from workflow enactment event logs. Wireless Netw 28, 1211–1218 (2022). https://doi.org/10.1007/s11276-018-01899-z

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  • DOI: https://doi.org/10.1007/s11276-018-01899-z

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