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Case Analytics Workbench: Platform for Hybrid Process Model Creation and Evolution

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Business Process Management (BPM 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9253))

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Abstract

Hybrid process models are considered an attractive approach for modeling knowledge-intensive processes. A hybrid process model combines both imperative and declarative modeling, which can handle both the structured and the flexible parts of a business process. However, it is difficult and time-consuming to create and refine a hybrid process model due to its structure complexity and case variability. This paper introduces the Case Analytics Workbench, an end-to-end system to accelerate hybrid process model creation and evolution by combining declarative and imperative process mining, event log clustering and human interaction in a cloud environment. We validated the effectiveness and applicability of our system by performing two case studies from insurance and health care industry respectively.

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References

  1. van der Aalst, W.M.P., et al.: Declarative workflows: Balancing between flexibility and support. Computer Science - Research and Development 23(2), 99–113 (2009)

    Article  Google Scholar 

  2. van der Aalst, W.M.P., Pesic, M., Schonenberg, H.: Declarative workflows: Balancing between flexibility and support. Computer Science - R&D 23(2), 99–113 (2009)

    Google Scholar 

  3. Hildebrandt, T., Mukkamala, R.R.: Declarative event-based workflow as distributed dynamic condition response graphs. Places 2010, 59–73 (2010)

    Google Scholar 

  4. Charfi, A., Mezini, M.: Hybrid web service composition: business processes meet business rules. In: 2nd International Conference on Service Oriented Computing, pp. 30–38. ACM, New York (2004)

    Google Scholar 

  5. Di Ciccio, C., et al.: Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches. Journal on Data Semantics (2014)

    Google Scholar 

  6. Clair, L.C., et al.: Dynamic Case Management — An Old Idea Catches New Fire. Forrester, Cambridge (2009)

    Google Scholar 

  7. Cull, R., Eldabi, T.: A hybrid approach to workflow modelling. Journal of Enterprise Information Management 23(3), 268–281 (2010)

    Article  Google Scholar 

  8. Damaggio, E., Hull, R., Vaculín, R.: On the equivalence of incremental and fixpoint semantics for business artifacts with guard-stage-milestone lifecycles. In: Rinderle-Ma, S., Toumani, F., Wolf, K. (eds.) BPM 2011. LNCS, vol. 6896, pp. 396–412. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  9. Davenport, T., Nohria, N.: Case Management and the Integration of Labor. MIT Sloan Management Review 35(2), 11–23 (1994)

    Google Scholar 

  10. Ester, M., et al.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: 2nd International Conference on Knowledge Discovery and Data Mining, pp. 226–231. AAAI Press (1996)

    Google Scholar 

  11. He, Y., et al.: MR-DBSCAN: an efficient parallel density-based clustering algorithm using mapreduce. In: Proceedings of the 2011 IEEE 17th International Conference on Parallel and Distributed Systems, pp. 473–480. IEEE Computer Society, Washington, DC (2011)

    Google Scholar 

  12. Hermans, V.C.T.: A hybrid process modeling approach. Eindhoven University of Technology (2014)

    Google Scholar 

  13. IBM: Case Manager. http://www-03.ibm.com/software/products/en/casemana (Accessed: March 13, 2015)

  14. IBM: IBM Bluemix. http://www-01.ibm.com/software/bluemix/ (Accessed: March 13, 2015)

  15. Montali, M.: Declarative Open Interaction Models. In: Montali, M. (ed.) Specification and Verification of Declarative Open Interaction Models. LNBIP, vol. 56, pp. 11–45. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  16. IBM: SQL Database. https://console.ng.bluemix.net/?ace_base=true/#/store/cloudOEPaneId=store&serviceOfferingGuid=0d5a104d-d700-4315-9b7c-8f84a9c85ae3&fromCatalog=true (Accessed: March 13, 2015)

  17. Krasner, G., Pope, S.: A Description of the Model-View-Controller User Interface Paradigm in the Smalltalk-80 System. Journal of Object Oriented Programming 1(3), 26–49 (1988)

    Google Scholar 

  18. Westergaard, M., Slaats, T.: CPN Tools 4: A Process Modeling Tool Combining Declarative and Imperative Paradigms. BPM Demos 2013 (2013)

    Google Scholar 

  19. Levenshtein, V.I.: Binary codes capable of correcting deletions, insertions, and reversals. Soviet Physics Doklady 10(8), 707–710 (1966)

    MathSciNet  Google Scholar 

  20. Li, X., et al.: Automatic variance analysis of multistage care pathways. In: Lovis, C., et al. (eds.) e-Health - For Continuity of Care - Proceedings of MIE 2014, the 25th European Medical Informatics Conference, August 31-September 3, Istanbul, Turkey, pp. 715–719 (2014)

    Google Scholar 

  21. Li, X., et al.: Mining temporal and data constraints associated with outcomes for care pathways. In: The 15th World Congress on Health and Biomedical Informatics, MEDINFO 2015 (Accepted)

    Google Scholar 

  22. Maggi, F.M., Dumas, M., García-Bañuelos, L., Montali, M.: Discovering data-aware declarative process models from event logs. In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 81–96. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  23. Maggi, F.M., Slaats, T., Reijers, H.A.: The automated discovery of hybrid processes. In: Sadiq, S., Soffer, P., Völzer, H. (eds.) BPM 2014. LNCS, vol. 8659, pp. 392–399. Springer, Heidelberg (2014)

    Google Scholar 

  24. Marin, M., et al.: Data centric BPM and the emerging case management standard: a short survey. In: La Rosa, M., Soffer, P. (eds.) Business Process Management Workshops. LNBIP, vol. 132, pp. 24–30. Springer, Heidelberg (2013)

    Google Scholar 

  25. De Masellis, R., Su, J.: Runtime enforcement of first-order LTL properties on data-aware business processes. In: Basu, S., Pautasso, C., Zhang, L., Fu, X. (eds.) ICSOC 2013. LNCS, vol. 8274, pp. 54–68. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  26. OASIS: Web Services Business Process Execution Language Version 2.0. OASIS

    Google Scholar 

  27. OMG: Business Process Model and Notation (BPMN), version 2.0.2. OMG (2014)

    Google Scholar 

  28. OMG: Case Management Model and Notation, version 1.0. OMG (2014)

    Google Scholar 

  29. Westergaard, M., Slaats, T.: Mixing paradigms for more comprehensible models. In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 283–290. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  30. Rabiner, L.R.: A tutorial on hidden markov models and selected applications in speech recognition. Proc. IEEE 77(2), 257–286 (1989)

    Google Scholar 

  31. Reijers, H.A., Slaats, T., Stahl, C.: Declarative modeling–an academic dream or the future for BPM? In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 307–322. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  32. Swenson, K.D.: Mastering the Unpredictable: How Adaptive Case Management Will Revolutionize the Way That Knowledge Workers Get Things Done. Meghan-Kiffer Press (2010)

    Google Scholar 

  33. Vaculin, R., et al.: Declarative business artifact centric modeling of decision and knowledge intensive business processes. In: The Fifteenth IEEE International Enterprise Computing Conference (EDOC 2011), pp. 151–160. IEEE (2011)

    Google Scholar 

  34. Weijters, A.J.M.M., Ribeiro, J.T.S.: Flexible Heuristics Miner (FHM). In: Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2011, Part of the IEEE Symposium Series on Computational Intelligence 2011, April 11-15, Paris, France, pp. 310–317 (2011)

    Google Scholar 

  35. WfMC: XML Process Definition Language (XPDL), vversion 2.2. Workflow Management Coalition (2012)

    Google Scholar 

  36. Zhu, W., et al.: Advanced Case Management with IBM Case Manager. IBM Redbooks (2012)

    Google Scholar 

  37. Hunt, S.A., Abraham, W.T., Chin, M.H., et al.: ACC/AHA 2005 guideline update for the diagnosis and management of chronic heart failure in the adult. Circulation 112(12), 154–235 (2005)

    Article  Google Scholar 

  38. Lakshmanan, G.T., Rozsnyai, S., Wang, F.: Investigating clinical care pathways correlated with outcomes. In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 323–338. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  39. Liu, H., Li, X., Yu, Y., Mei, J., Xie, G., Perer, A., Fei, W., Hu, J.: Synthesizing analytic evidences to refine care pathways. In: Medical Informatics Europe Conference (2015)

    Google Scholar 

  40. Becker, M., Laue, R.: A comparative survey of business process similarity measures. Computers in Industry 63(2), 148–167 (2012)

    Google Scholar 

  41. Ekanayake, C., Dumas, M., García-Bañuelos, L., La Rosa, M.: Slice, Mine and Dice: Complexity-Aware Automated Discovery of Business Process Models. In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 49–64. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

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Author information

Authors and Affiliations

  1. IBM Research, Beijing, China

    Yiqin Yu, Xiang Li, Haifeng Liu, Jing Mei & Guotong Xie

  2. IBM Analytics Group, Tarrytown, NY, USA

    Nirmal Mukhi

  3. IBM T.J. Watson Research Center, Cambridge, MA, USA

    Vatche Ishakian

  4. IBM Analytics Group, Costa Mesa, CA, USA

    Mike Marin

  5. Audible, Inc., Cambridge, MA, USA

    Geetika T. Lakshmanan

Authors
  1. Yiqin Yu
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  2. Xiang Li
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  3. Haifeng Liu
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  4. Jing Mei
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  5. Nirmal Mukhi
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  6. Vatche Ishakian
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  7. Guotong Xie
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  8. Geetika T. Lakshmanan
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  9. Mike Marin
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Corresponding author

Correspondence to Yiqin Yu .

Editor information

Editors and Affiliations

  1. IBM Almaden Research Center, San Jose, California, USA

    Hamid Reza Motahari-Nezhad

  2. Queensland University, Brisbane, Queensland, Australia

    Jan Recker

  3. Humboldt-Universität zu Berlin, Berlin, Germany

    Matthias Weidlich

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Yu, Y. et al. (2015). Case Analytics Workbench: Platform for Hybrid Process Model Creation and Evolution. In: Motahari-Nezhad, H., Recker, J., Weidlich, M. (eds) Business Process Management. BPM 2016. Lecture Notes in Computer Science(), vol 9253. Springer, Cham. https://doi.org/10.1007/978-3-319-23063-4_16

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  • DOI: https://doi.org/10.1007/978-3-319-23063-4_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23062-7

  • Online ISBN: 978-3-319-23063-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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