Activity Matching with Human Intelligence

  • Carlos RodríguezEmail author
  • Christopher Klinkmüller
  • Ingo Weber
  • Florian Daniel
  • Fabio Casati
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 260)


Effective matching of activities is the first step toward successful process model matching and search. The problem is nontrivial and has led to a variety of computational similarity metrics and matching approaches, however all still with low performance in terms of precision and recall. In this paper, instead, we study how to leverage on human intelligence to identify matches among activities and show that the problem is not as straightforward as most computational approaches assume. We access human intelligence (i) by crowdsourcing the activity matching problem to generic workers and (ii) by eliciting ground truth matches from experts. The precision and recall we achieve and the qualitative analysis of the results testify huge potential for a human-based activity matching that contemplates disagreement and interpretation.


Activity matching Label matching Crowdsourcing 



We would like to thank M. Vitali, G. Meroni, P. Plebani (Politecnico di Milano) and S. Tranquillini and J. Stevovic (Chino, Trento) for their help with the creation of the ground truth matchings for the experiments.


  1. 1.
    Allahbakhsh, M., Benatallah, B., Ignjatovic, A., Motahari-Nezhad, H., Bertino, E., Dustdar, S.: Quality control in crowdsourcing systems: issues and directions. IEEE Internet Comput. 17(2), 76–81 (2013)CrossRefGoogle Scholar
  2. 2.
    Antunes, G., et al.: The process model matching contest 2015. In: EMISA (2015)Google Scholar
  3. 3.
    Castelo Branco, M., Troya, J., Czarnecki, K., Küster, J., Völzer, H.: Matching business process workflows across abstraction levels. In: France, R.B., Kazmeier, J., Breu, R., Atkinson, C. (eds.) MODELS 2012. LNCS, vol. 7590, pp. 626–641. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  4. 4.
    Cavallo, R., Jain, S.: Efficient crowdsourcing contests. Proc. AAMAS 2, 677–686 (2012)Google Scholar
  5. 5.
    Cayoglu, U. et al.: The process model matching contest 2013. In: PMC-MR (2013)Google Scholar
  6. 6.
    Dijkman, R., Dumas, M., García-Bañuelos, L.: Graph matching algorithms for business process model similarity search. In: Dayal, U., Eder, J., Koehler, J., Reijers, H.A. (eds.) BPM 2009. LNCS, vol. 5701, pp. 48–63. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  7. 7.
    Dijkman, R., Dumas, M., Garcia-Banuelos, L., Kaarik, R.: Aligning business process models. In: EDOC 2009, pp. 45–53 (2009)Google Scholar
  8. 8.
    Dijkman, R., Dumas, M., van Dongen, B., Käärik, R., Mendling, J.: Similarity of business process models: metrics and evaluation. Inf. Syst. 36(2), 498–516 (2011)CrossRefGoogle Scholar
  9. 9.
    Dumas, M., García-Bañuelos, L., Dijkman, R.M.: Similarity search of business process models. IEEE Data Eng. Bull. 32(3), 23–28 (2009)Google Scholar
  10. 10.
    Ekanayake, C.C., Dumas, M., García-Bañuelos, L., La Rosa, M., ter Hofstede, A.H.M.: Approximate clone detection in repositories of business process models. In: Barros, A., Gal, A., Kindler, E. (eds.) BPM 2012. LNCS, vol. 7481, pp. 302–318. Springer, Heidelberg (2012)Google Scholar
  11. 11.
    Euzenat, J., Shvaiko, P.: Ontology Matching. Springer, Secaucus (2007)zbMATHGoogle Scholar
  12. 12.
    Grigori, D., Corrales, J.C., Bouzeghoub, M.: Behavioral matchmaking for service retrieval. In: IEEE ICWS, pp. 145–152 (2006)Google Scholar
  13. 13.
    Howe, J.: Crowdsourcing: Why the Power of the Crowd Is Driving the Future of Business, 1st edn. Crown Publishing Group, New York (2008)Google Scholar
  14. 14.
    Ipeirotis, P.G.: Analyzing the amazon mechanical turk marketplace. XRDS 17(2), 16–21 (2010)CrossRefGoogle Scholar
  15. 15.
    Jin, T., Wang, J., Rosa, M.L., ter Hofstede, A.H., Wen, L.: Efficient querying of large process model repositories. Comput. Ind. 64(1), 41–49 (2013)CrossRefGoogle Scholar
  16. 16.
    Klinkmüller, C., Leopold, H., Weber, I., Mendling, J., Ludwig, A.: Listen to me: improving process model matching through user feedback. In: Sadiq, S., Soffer, P., Völzer, H. (eds.) BPM 2014. LNCS, vol. 8659, pp. 84–100. Springer, Heidelberg (2014)Google Scholar
  17. 17.
    Klinkmüller, C., Weber, I., Mendling, J., Leopold, H., Ludwig, A.: Increasing recall of process model matching by improved activity label matching. In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 211–218. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  18. 18.
    Koschmider, A., Blanchard, E.: User assistance for business process model decomposition. In: IEEE RCIS, pp. 445–454 (2007)Google Scholar
  19. 19.
    Kunze, M., Weidlich, M., Weske, M.: Behavioral similarity – a proper metric. In: Rinderle-Ma, S., Toumani, F., Wolf, K. (eds.) BPM 2011. LNCS, vol. 6896, pp. 166–181. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  20. 20.
    Leopold, H., Niepert, M., Weidlich, M., Mendling, J., Dijkman, R., Stuckenschmidt, H.: Probabilistic optimization of semantic process model matching. In: Barros, A., Gal, A., Kindler, E. (eds.) BPM 2012. LNCS, vol. 7481, pp. 319–334. Springer, Heidelberg (2012)Google Scholar
  21. 21.
    Sakr, S., Awad, A., Kunze, M.: Querying process models repositories by aggregated graph search. In: Rosa, M., Soffer, P. (eds.) BPM Workshops 2012. LNBIP, vol. 132, pp. 573–585. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  22. 22.
    Satzger, B., Psaier, H., Schall, D., Dustdar, S.: Auction-based crowdsourcing supporting skill management. Inf. Syst. 38(4), 547–560 (2013)CrossRefGoogle Scholar
  23. 23.
    Weidlich, M., Dijkman, R., Mendling, J.: The ICoP framework: identification of correspondences between process models. In: Pernici, B. (ed.) CAiSE 2010. LNCS, vol. 6051, pp. 483–498. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  24. 24.
    Weidlich, M., Sagi, T., Leopold, H., Gal, A., Mendling, J.: Predicting the quality of process model matching. In: Daniel, F., Wang, J., Weber, B. (eds.) BPM 2013. LNCS, vol. 8094, pp. 203–210. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  25. 25.
    Weidlich, M., Sheetrit, E., Branco, M.C., Gal, A.: Matching business process models using positional passage-based language models. In: ER 2013, pp. 130–137 (2013)Google Scholar
  26. 26.
    Zha, H., Wang, J., Wen, L., Wang, C., Sun, J.: A workflow net similarity measure based on transition adjacency relations. Comput. Ind. 61(5), 463–471 (2010)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Carlos Rodríguez
    • 1
    Email author
  • Christopher Klinkmüller
    • 2
    • 3
  • Ingo Weber
    • 3
    • 4
  • Florian Daniel
    • 5
  • Fabio Casati
    • 1
  1. 1.University of TrentoPovoItaly
  2. 2.Department of ComputingMacquarie UniversitySydneyAustralia
  3. 3.Data61, CSIROSydneyAustralia
  4. 4.University of New South WalesSydneyAustralia
  5. 5.Politecnico di MilanoMilanoItaly

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