Skip to main content
SpringerLink
Log in

Discovering the “Glue” Connecting Activities

Exploiting Monotonicity to Learn Places Faster

  • Chapter
  • First Online:
Book cover It's All About Coordination

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10865))

Abstract

Process discovery, one of the key areas within process mining, aims to derive behavioral models from event data. Since event logs are inherently incomplete (containing merely example behaviors) and unbalanced, this is often challenging. Different target languages can be used to capture sequential, conditional, concurrent, and iterative behaviors. In this paper, we assume that a process model is merely a set of places (like in Petri nets). Given a particular behavior, a place can be “fitting”, “underfed” (tokens are missing), or “overfed” (tokens are remaining). We define a partial order on places based on their connections. Then we will show various monotonicity properties that can be exploited during process discovery. If a candidate place is underfed, then all “lighter” places are also underfed. If a candidate place is overfed, then all “heavier” places are also overfed. This allows us to prune the search space dramatically. Moreover, we can further reduce the search space by not allowing conflicting or redundant places. These more foundational insights can be used to develop fast process mining algorithms producing places with a guaranteed quality level.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. van der Aalst, W.M.P.: Decomposing Petri nets for process mining: a generic approach. Distrib. Parallel Databases 31(4), 471–507 (2013)

    Article  Google Scholar 

  2. van der Aalst, W.M.P.: Mediating between modeled and observed behavior: the quest for the “Right” process. In: IEEE International Conference on Research Challenges in Information Science (RCIS 2013), pp. 31–43. IEEE Computing Society (2013)

    Google Scholar 

  3. van der Aalst, W.M.P.: Process Mining: Data Science in Action. Springer, Berlin (2016). https://doi.org/10.1007/978-3-662-49851-4

    Book  Google Scholar 

  4. van der Aalst, W.M.P., Adriansyah, A., van Dongen, B.: Replaying history on process models for conformance checking and performance analysis. WIREs Data Mining Knowl. Discov. 2(2), 182–192 (2012)

    Article  Google Scholar 

  5. van der Aalst, W.M.P., van Hee, K.M., ter Hofstede, A.H.M., Sidorova, N., Verbeek, H.M.W., Voorhoeve, M., Wynn, M.T.: Soundness of workflow nets: classification, decidability, and analysis. Formal Aspects Comput. 23(3), 333–363 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  6. van der Aalst, W.M.P., De Masellis, R., Di Francescomarino, C., Ghidini, C.: Learning hybrid process models from events. In: Carmona, J., Engels, G., Kumar, A. (eds.) BPM 2017. LNCS, vol. 10445, pp. 59–76. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-65000-5_4

    Chapter  Google Scholar 

  7. van der Aalst, W.M.P., Rubin, V., Verbeek, H.M.W., van Dongen, B.F., Kindler, E., Günther, C.W.: Process mining: a two-step approach to balance between underfitting and overfitting. Softw. Syst. Model. 9(1), 87–111 (2010)

    Article  Google Scholar 

  8. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In: Proceedings of the 20th International Conference on Very Large Data Bases (VLDB), pp. 487–499. Morgan Kaufmann Publishers Inc., Santiago de Chile (1994)

    Google Scholar 

  9. Agrawal, R., Srikant, R.: Mining sequential patterns. In: Proceedings of the 11th International Conference on Data Engineering (ICDE 1995), pp. 3–14. IEEE Computer Society (1995)

    Google Scholar 

  10. Arbab, F.: Reo: a channel-based coordination model for component composition. Math. Struct. Comput. Sci. 14(3), 329–366 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  11. Bergenthum, R., Desel, J., Lorenz, R., Mauser, S.: Process mining based on regions of languages. In: Alonso, G., Dadam, P., Rosemann, M. (eds.) BPM 2007. LNCS, vol. 4714, pp. 375–383. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-75183-0_27

    Chapter  Google Scholar 

  12. Cortadella, J., Kishinevsky, M., Lavagno, L., Yakovlev, A.: Deriving Petri nets from finite transition systems. IEEE Trans. Comput. 47(8), 859–882 (1998)

    Article  MathSciNet  Google Scholar 

  13. Desel, J., Esparza, J.: Free Choice Petri Nets, Volume 40 of Cambridge Tracts in Theoretical Computer Science. Cambridge University Press, Cambridge (1995)

    Google Scholar 

  14. Ehrenfeucht, A., Rozenberg, G.: Partial (set) 2-structures - part 1 and part 2. Acta Inform. 27(4), 315–368 (1989)

    Article  MATH  Google Scholar 

  15. Günther, C.W., van der Aalst, W.M.P.: Fuzzy mining: adaptive process simplification based on multi-perspective metrics. In: Alonso, G., Dadam, P., Rosemann, M. (eds.) International Conference on Business Process Management (BPM 2007). LNCS, vol. 4714, pp. 328–343. Springer-Verlag, Berlin (2007). https://doi.org/10.1007/978-3-540-75183-0_24

    Google Scholar 

  16. Jongmans, S.S.T.Q., Arbab, F.: Overview of thirty semantic formalisms for Reo. Sci. Ann. Comput. Sci. 22(1), 201–251 (2012)

    MathSciNet  Google Scholar 

  17. 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. LNBIP, vol. 171, pp. 66–78. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-06257-0_6

    Chapter  Google Scholar 

  18. Leemans, S.J.J., Fahland, D., van der Aalst, W.M.P.: Discovering block-structured process models from incomplete event logs. In: Ciardo, G., Kindler, E. (eds.) PETRI NETS 2014. LNCS, vol. 8489, pp. 91–110. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07734-5_6

    Chapter  Google Scholar 

  19. Leemans, S.J.J., Fahland, D., van der Aalst, W.M.P.: Scalable process discovery with guarantees. In: Gaaloul, K., Schmidt, R., Nurcan, S., Guerreiro, S., Ma, Q. (eds.) CAISE 2015. LNBIP, vol. 214, pp. 85–101. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-19237-6_6

    Chapter  Google Scholar 

  20. Mannila, H., Toivonen, H., Verkamo, A.I.: Discovery of frequent episodes in event sequences. Data Mining Knowl. Discov. 1(3), 259–289 (1997)

    Article  Google Scholar 

  21. Meng, S., Arbab, F., Baier, C.: Synthesis of Reo circuits from scenario-based interaction specifications. Sci. Comput. Program. 76(8), 651–680 (2011)

    Article  MATH  Google Scholar 

  22. Sole, M., Carmona, J.: Process mining from a basis of regions. In: Lilius, J., Penczek, W. (eds.) Applications and Theory of Petri Nets 2010. LNCS, vol. 6128, pp. 226–245. Springer, Berlin (2010). https://doi.org/10.1007/978-3-642-13675-7_14

    Chapter  Google Scholar 

  23. Tax, N., Lu, X., Sidorova, N., Fahland, D., van der Aalst, W.M.P.: The imprecisions of precision measures in process mining. Inf. Process. Lett. 135, 1–8 (2018)

    Google Scholar 

  24. Weijters, A.J.M.M., van der Aalst, W.M.P.: Rediscovering workflow models from event-based data using little thumb. Integrated Comput.-Aided Eng. 10(2), 151–162 (2003)

    Google Scholar 

  25. van der Werf, J.M.E.M., van Dongen, B.F., Hurkens, C.A.J., Serebrenik, A.: Process discovery using integer linear programming. Fundamenta Inform. 94, 387–412 (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Process and Data Science (PADS), RWTH Aachen University, Aachen, Germany

    Wil M. P. van der Aalst

Authors
  1. Wil M. P. van der Aalst
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wil M. P. van der Aalst .

Editor information

Editors and Affiliations

  1. Centre for Mathematics and Computer Science, Amsterdam, The Netherlands

    Frank de Boer

  2. Leiden University, Leiden, The Netherlands

    Marcello Bonsangue

  3. Centre for Mathematics and Computer Science, Amsterdam, The Netherlands

    Jan Rutten

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

van der Aalst, W.M.P. (2018). Discovering the “Glue” Connecting Activities. In: de Boer, F., Bonsangue, M., Rutten, J. (eds) It's All About Coordination. Lecture Notes in Computer Science(), vol 10865. Springer, Cham. https://doi.org/10.1007/978-3-319-90089-6_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-90089-6_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-90088-9

  • Online ISBN: 978-3-319-90089-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation