DOI QR코드

DOI QR Code

A Conceptual Approach for Discovering Proportions of Disjunctive Routing Patterns in a Business Process Model

  • Received : 2016.10.20
  • Accepted : 2017.01.06
  • Published : 2017.02.28

Abstract

The success of a business process management system stands or falls on the quality of the business processes. Many experiments therefore have been devoting considerable attention to the modeling and analysis of business processes in process-centered organizations. One of those experiments is to apply the probabilistic theories to the analytical evaluations of business process models in order to improve their qualities. In this paper, we excogitate a conceptual way of applying a probability theory of proportions into modeling business processes. There are three types of routing patterns such as sequential, disjunctive, conjunctive and iterative routing patterns in modeling business processes, into which the proportion theory is applicable. This paper focuses on applying the proportion theory to the disjunctive routing patterns, in particular, and formally named proportional information control net that is the formal representation of a corresponding business process model. In this paper, we propose a conceptual approach to discover a proportional information control net from the enactment event histories of the corresponding business process, and describe the details of a series of procedural frameworks and operational mechanisms formally and graphically supporting the proposed approach. We strongly believe that the conceptual approach with the proportional information control net ought to be very useful to improve the quality of business processes by adapting to the reengineering and redesigning the corresponding business processes.

Keywords

References

  1. Daniela Grigori, Fabio Casati, Malu Castellanos, Umeshwar Dayal, Mehmet Sayal and Ming-Chien Shan, "Business Process Intelligence," JORNAL OF COMPUTERS IN INDUSTRY, Vol. 53, Issue 3, 2004.
  2. Fabio Casati, et al, "Business Process Intelligence," Technical Report, HPL-2002-119, HP Laboratories Palo Alto, 2002.
  3. Kwang-Hoon Kim and Clarence A. Ellis, "Workflow Reduction for Reachable-path Rediscovery in Workflow Mining," Series of Studies in Computational Intelligence: the Foundations and Novel Approaches in Data Mining, Vol. 9, pp.289-310, Springer, 2006.
  4. Kwang-Hoon Kim, "Control-path Oriented Workflow Intelligence Analysis on Enterprise Workflow Grids," in Proc. of the International Conference on Semantics, Knowledge, and Grid, Beijing, China, 2005.
  5. W. M. P. van der Aalst, B. F. van Dongena; J. Herbst, L. Marustera, G. Schimm and A. J. M. M. Weijters, "Workflow mining: A survey of issues and approaches," JOURNAL OF DATA AND KNOWLEDGE ENGINEERING, Vol. 47, Issue 2, pp. 237-267, 2003. https://doi.org/10.1016/S0169-023X(03)00066-1
  6. W. M. P. van der Aalst and A. J. M. M. Weijters, "Process mining: a research agenda," Journal of Computers in Industry, Vol. 53, Issue 3, 2004.
  7. Aalst, W.P.M., Alves de Medeiros, A.K., and Weijters, A.J.M.M., "Process Equivalence: Comparing Two Process Models Based on Observed Behavior," BPM2006, Lecture Notes in Computer Science, Vol. 4102, pp. 129-144, 2006.
  8. Ahn, H. and Kim, K., "A Stochastic Activity-to-Performer Affiliation Binding Formalism in ICN-based Workflow Models," ICICI Express Letters, Vol. 9, No. 12, 2015.
  9. Ellis, C.A. "Information Control Nets: A Mathematical Model of Office Information Flow," The Proceedings of the Ninth Annual ACM Conference on Simulation, Measurement, and Modeling of Computer Systems, 1979.
  10. Ellis, Clarence A., Kim, K., Rembert, A., Wainer, J., "Investigations on Stochastic Information Control Nets," INFORMATION SCIENCES, Vol. 194, pp. 120-137, 2012. https://doi.org/10.1016/j.ins.2011.07.031
  11. Kim, H., Ahn, H. and Kim, P. K, "Modeling, Discovering, and Visualizing Workflow Performer-Role Affiliation Networking Knowledge," KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, vol. 8, no. 2, pp. 689-706, 2014. https://doi.org/10.3837/tiis.2014.02.022
  12. Kim, J., Ahn, H., Park, M., Kim, S., and Kim, K. P., "An Estimated Closeness Centrality Ranking Algorithm and Its Performance Analysis in Large-Scale Workflow-supported Social Networks," KSII Transactions on Internet and Information Systems, 10, 3, 1454-1466, 2016. https://doi.org/10.3837/tiis.2016.03.031
  13. Kim, Kwanghoon, "A XML-Based Workflow Event Logging Mechanism for Workflow Mining," in Proc. of the International Workshop on APWeb, pages 132-136, 2006.
  14. Kim, Kwanghoon and Ellis, Clarence A., "${\sigma}$-Algorithm: Structured Workflow Process Mining Through Amalgamating Temporal Workcases," in Proc. of PAKDD2007, Advances in Knowledge Discovery and Data Mining, Lecture Notes in Artificial Intelligence, Vol. 4426, pp. 119-130, 2007.
  15. Kim, Kwanghoon Pio, "Discovering Activity-Performer Affiliation Knowledge on ICN-based Workflow Models," JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, Vol. 29, No. 1, pp. 79-97, 2013.
  16. Kim, Kwanghoon Pio, "Human-Centered Workflow Intelligence," in Proc. of Tutorial at the International Conference on Advanced Communications Technology, Phoenix Park, Pyeongchang, South Korea, Feb. 2014.
  17. Kim, Kwanghoon Pio, "A Stochastic Workflow Performer-to-Activity Affiliation Network Model," in Proc. of the 28th Annual Conference of Biomedical Fuzzy System Association (BMFSA2015), Kumamoto, Japan, 21-22 Nov. 2015.
  18. Kim, K., Paik, S, and Ellis, C., "Actor-Oriented Workflow Model," in Proc. of the Second International Symposium on Cooperative Database Systems for Advanced Applications (CODAS'99), Wollongong, Australia, March 27-28, pp. 150-164, Springer, Singapore, ISBN 9814021644, 1999.
  19. Kim, Kwanghoon and Ellis, Clarence A., "Section II / Chapter VII. An ICN-based Work- flow Model and Its Advances," HANDBOOK OF RESEARCH ON BUSINESS PROCESS MODELING, pp. 142-172, IGI Global, ISR, 2009.
  20. Lei, Y., and Singh, M.P., "A Comparison of Workflow Metamodels," in Proc. of the ER-97 Workshop on Behavioral Modeling and Design Transformations, Los Angeles, USA, November 1997.
  21. Park, Minjae and Kim, Kwanghoon, "Control-path Oriented Workflow Intelligence Analyses," JOURNAL OF INFORMATION SCIENCE AND ENGINEERING, Vol. 24, No. 2, pp. 343-359, 2008.
  22. Snijders, Tom A.B. , Bunt, Gerhard G. van de, Steglich, Christian E.G., "Introduction to Stochastic Actor-Based Models for Network Dynamics," SOCIAL NETWORKS, Vol. 32, pp. 44-60, 2010. https://doi.org/10.1016/j.socnet.2009.02.004
  23. Varacca, D. and Nielsen, M., "Probabilistic Petri Nets and Mazurkiewicz Equivalence," in Proc. of the Conference on Decision and Control, vol. 5, pp. 4104-4109, 2001.

Cited by

  1. 맵리듀스기반 워크플로우 빅-로그 클러스터링 기법 vol.20, pp.1, 2017, https://doi.org/10.7472/jksii.2019.20.1.87
  2. HBase based Business Process Event Log Schema Design of Hadoop Framework vol.20, pp.5, 2019, https://doi.org/10.7472/jksii.2019.20.5.49
  3. 액티비티별 특징 정규화를 적용한 LSTM 기반 비즈니스 프로세스 잔여시간 예측 모델 vol.21, pp.3, 2017, https://doi.org/10.7472/jksii.2020.21.3.83