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Log Delta Analysis: Interpretable Differencing of Business Process Event Logs

  • Nick R. T. P. van BeestEmail author
  • Marlon Dumas
  • Luciano García-Bañuelos
  • Marcello La Rosa
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9253)

Abstract

This paper addresses the problem of explaining behavioral differences between two business process event logs. The paper presents a method that, given two event logs, returns a set of statements in natural language capturing behavior that is present or frequent in one log, while absent or infrequent in the other. This log delta analysis method allows users to diagnose differences between normal and deviant executions of a process or between two versions or variants of a process. The method relies on a novel approach to losslessly encode an event log as an event structure, combined with a frequency-enhanced technique for differencing pairs of event structures. A validation of the proposed method shows that it accurately diagnoses typical change patterns and can explain differences between normal and deviant cases in a real-life log, more compactly and precisely than previously proposed methods.

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References

  1. 1.
    Nguyen, H., Dumas, M., La Rosa, M., Maggi, F.M., Suriadi, S.: Mining business process deviance: a quest for accuracy. In: Meersman, R., Panetto, H., Dillon, T., Missikoff, M., Liu, L., Pastor, O., Cuzzocrea, A., Sellis, T. (eds.) OTM 2014. LNCS, vol. 8841, pp. 436–445. Springer, Heidelberg (2014) Google Scholar
  2. 2.
    Suriadi, S., Wynn, M.T., Ouyang, C., ter Hofstede, A.H.M., van Dijk, N.J.: Understanding process behaviours in a large insurance company in australia: a case study. In: Salinesi, C., Norrie, M.C., Pastor, Ó. (eds.) CAiSE 2013. LNCS, vol. 7908, pp. 449–464. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  3. 3.
    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) CrossRefGoogle Scholar
  4. 4.
    Günther, C.W., Rozinat, A.: Disco: discover your processes. In: BPM 2012 Demos, CEUR, pp. 40–44 (2012)Google Scholar
  5. 5.
    Nielsen, M., Plotkin, G.D., Winskel, G.: Petri Nets, Event Structures and Domains, Part I. TCS 13, 85–108 (1981)zbMATHMathSciNetCrossRefGoogle Scholar
  6. 6.
    Armas-Cervantes, A., Baldan, P., Dumas, M., García-Bañuelos, L.: Behavioral comparison of process models based on canonically reduced event structures. In: Sadiq, S., Soffer, P., Völzer, H. (eds.) BPM 2014. LNCS, vol. 8659, pp. 267–282. Springer, Heidelberg (2014) Google Scholar
  7. 7.
    Weber, B., Reichert, M., Rinderle-Ma, S.: Change patterns and change support features: Enhancing flexibility in process-aware information systems. DKE 66(3), 438–466 (2008)CrossRefGoogle Scholar
  8. 8.
    Partington, A., Wynn, M.T., Suriadi, S., Ouyang, C., Karnon, J.: Process mining of clinical processes: Comparative analysis of four australian hospitals. In: ACM TMIS (2014) (In press)Google Scholar
  9. 9.
    Jagadeesh Chandra Bose, R.P., van der Aalst, W.M.P.: Abstractions in process mining: a taxonomy of patterns. In: Dayal, U., Eder, J., Koehler, J., Reijers, H.A. (eds.) BPM 2009. LNCS, vol. 5701, pp. 159–175. Springer, Heidelberg (2009) CrossRefGoogle Scholar
  10. 10.
    Swinnen, J., Depaire, B., Jans, M.J., Vanhoof, K.: A process deviation analysis – a case study. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds.) BPM Workshops 2011, Part I. LNBIP, vol. 99, pp. 87–98. Springer, Heidelberg (2012) CrossRefGoogle Scholar
  11. 11.
    Lo, D., Cheng, H., Han, J., Khoo, S.C., Sun, C.: Classification of software behaviors for failure detection: a discriminative pattern mining approach. In: KDD 2009, pp. 557–566. ACM (2009)Google Scholar
  12. 12.
    Weidlich, M., Mendling, J., Weske, M.: Efficient Consistency Measurement Based on Behavioral Profiles of Process Models. IEEE TSE 37(3), 410–429 (2011)MathSciNetGoogle Scholar
  13. 13.
    Cook, J.E., Wolf, A.L.: Event-base detection of concurrency. In: FSE 1998, pp. 35–45. ACM (1998)Google Scholar
  14. 14.
    van der Aalst, W.M.P., Weijters, T., Maruster, L.: Workflow mining: discovering process models from event logs. IEEE TKDE 16(9), 1128–1142 (2004)Google Scholar
  15. 15.
    Dumas, M., La Rosa, M., Mendling, J., Reijers, H.: Fundamentals of Business Process Management. Springer (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Nick R. T. P. van Beest
    • 1
    • 3
    Email author
  • Marlon Dumas
    • 2
  • Luciano García-Bañuelos
    • 2
  • Marcello La Rosa
    • 3
    • 1
  1. 1.NICTABrisbaneAustralia
  2. 2.University of TartuTartuEstonia
  3. 3.Queensland University of TechnologyBrisbaneAustralia

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