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Correlating Unlabeled Events from Cyclic Business Processes Execution

  • Dina BayomieEmail author
  • Ahmed Awad
  • Ehab Ezat
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9694)

Abstract

Event logs are invaluable sources about the actual execution of processes. Most of process mining and postmortem analysis techniques depend on logs. All these techniques require the existence of the case ID to correlate the events. Real life logs are rarely originating from a centrally orchestrated process execution. Hence, case ID is missing, known as unlabeled logs. Correlating unlabeled events is a challenging problem that has received little attention in literature. Moreover, the few approaches addressing this challenge support acyclic business processes only. In this paper, we build on our previous work and propose an approach to deduce case ID for unlabeled event logs produced from cyclic business processes. As a result, a set of ranked labeled logs are generated. We evaluate our approach using real life logs.

Keywords

Unlabeled event log Event correlation Cyclic processes loops Process mining 

References

  1. 1.
    der Aalst, W.V.: Process Mining: Discovery Conformance and Enhancement of Business Processes. Springer, Heidelberg (2011)CrossRefzbMATHGoogle Scholar
  2. 2.
    van de Aalst, W., et al.: Process mining manifesto. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds.) BPM Workshops 2011, Part I. LNBIP, vol. 99, pp. 169–194. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  3. 3.
    Baier, T., Di Ciccio, C., Mendling, J., Weske, M.: Matching of events and activities - an approach using declarative modeling constraints. In: Gaaloul, K., Schmidt, R., Nurcan, S., Guerreiro, S., Ma, Q. (eds.) BPMDS 2015 and EMMSAD 2015. LNBIP, vol. 214, pp. 119–134. Springer, Heidelberg (2015)CrossRefGoogle Scholar
  4. 4.
    Bayomie, D., Helal, I.M.A., Awad, A., Ezat, E., ElBastawissi, A.: Deducing case IDs for unlabeled event logs. In: BPI workshop, BPM (2015)Google Scholar
  5. 5.
    Dustdar, S., Gombotz, R.: Discovering web service workflows using web services interaction mining. IJBPIM 1(4), 256 (2006)CrossRefGoogle Scholar
  6. 6.
    Ferreira, D.R., Gillblad, D.: Discovering process models from unlabelled event logs. In: Dayal, U., Eder, J., Koehler, J., Reijers, H.A. (eds.) BPM 2009. LNCS, vol. 5701, pp. 143–158. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  7. 7.
    Herzberg, N., Kunze, M., Rogge-Solti, A.: Towards process evaluation in non-automated process execution environments. In: CEUR Workshop Proceedings on ZEUS, vol. 847, pp. 97–103 (2012). http://www.CEUR-WS.org
  8. 8.
    Leemans, S.J.J., Fahland, D., van der Aalst, W.M.P.: Discovering block-structured process models from event logs containing infrequent behaviour. In: Lohmann, N., Song, M., Wohed, P. (eds.) BPM 2013 Workshops. LNBIP, vol. 171, pp. 66–78. Springer, Heidelberg (2014)CrossRefGoogle Scholar
  9. 9.
    Mendling, J., Reijers, H.A., van der Aalst, W.M.P.: Seven Process Modeling Guidelines (7PMG). Inf. Softw. Technol. 52(2), 127–136 (2010)CrossRefGoogle Scholar
  10. 10.
    de Murillas, E.G.L., van der Aalst, W.M.P., Reijers, H.A.: Process mining on databases: unearthing historical data from redo logs. In: Motahari-Nezhad, H.R., Recker, J., Weidlich, M. (eds.) BPM. LNCS, vol. 9253, pp. 367–385. Springer, New York (2015)CrossRefGoogle Scholar
  11. 11.
    Nezhad, H.R.M., Saint-Paul, R., Casati, F., Benatallah, B.: Event correlation for process discovery from web service interaction logs. VLDB J. 20(3), 417–444 (2011)CrossRefGoogle Scholar
  12. 12.
    Pourmirza, S., Dijkman, R., Grefen, P.: Correlation mining: mining process orchestrations without case identifiers. In: Barros, A., et al. (eds.) ICSOC 2015. LNCS, vol. 9435, pp. 237–252. Springer, Heidelberg (2015). doi: 10.1007/978-3-662-48616-0_15 CrossRefGoogle Scholar
  13. 13.
    Rose, D.J., Tarjan, R.E.: Algorithmic aspects of vertex elimination. In: Proceedings of the 7th Annual ACM Symposium on Theory of Computing, pp. 245–254 (1975)Google Scholar
  14. 14.
    Suriadi, S., Ouyang, C., van der Aalst, W.M., ter Hofstede, A.H.: Event gap analysis: understanding why processes take time. Technical report, QUT: ePrints (2014)Google Scholar
  15. 15.
    Van Der Aalst, W.M.P., Van Dongen, B.F., Günther, C., Rozinat, A., Verbeek, H.M.W., Weijters, A.: Prom: the process mining toolkit. In: CEUR Workshop Proceedings, vol. 489 (2009). http://www.CEUR-WS.org
  16. 16.
    Walicki, M., Ferreira, D.R.: Sequence partitioning for process mining with unlabeled event logs. Data Knowl. Eng. 70(10), 821–841 (2011)CrossRefGoogle Scholar
  17. 17.
    Weidlich, M.: Behavioral profiles - a relational approach to behaviour consistency. Ph.D. thesis. University of Potsdam (2011)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Information Systems Department, Faculty of Computers and InformationCairo UniversityGizaEgypt

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