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Tree Automata Mining

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Computational Intelligence (IJCCI 2013)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 613))

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Abstract

This paper [The article is an essentially revised version of conference paper (Przybylek (2013) International Conference on Evolutionary Computation Theory and Applications)] describes a new approach to mine business processes. We define bidirectional tree languages together with their finite models and show how they represent business processes. We offer an algebraic explanation for the phenomenon of an evolutionary metaheuristic “skeletal algorithms”, and show how this explanation gives rise to algorithms for recognition of bidirectional tree automata. We use the algorithms in process mining and in discovering mathematical theories.

This work has been partially supported by Polish National Science Center, project DEC-2011/01/N/ST6/02752.

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References

  1. Bremermann, H.J.; Optimization through evolution and recombination. In: Yovitts, M.C. et al. (eds.) Self-Organizing Systems 1962, p. 93106. Spartan Books, Washington (1962)

    Google Scholar 

  2. Comon, H., Dauchet, M., Gilleron, R., Löding, C., Jacquemard, F., Lugiez, D., Tison, S., Tommasi, M.: Tree automata techniques and applications (2007)

    Google Scholar 

  3. de Medeiros, A., van Dongen, B., van der Aalst, W., Weijters, A.: Process mining: extending the alpha-algorithm to mine short loops. In BETA Working Paper Series, Eindhoven. Eindhoven University of Technology (2004)

    Google Scholar 

  4. Friedberg, R.M.: A learning machines part I. IBM J. Res. Dev. 2 (1956)

    Article  MathSciNet  Google Scholar 

  5. Friedberg, R.M., Dunham, B., North, J.H.: A learning machines part II. IBM J. Res. Dev. 3 (1959)

    Article  MathSciNet  Google Scholar 

  6. Holland, J.H.: Adaption in Natural and Artificial Systems. The University of Michigan Press, Ann Arbor (1975)

    Google Scholar 

  7. Przybylek, M.R.: Skeletal algorithms in process mining. In: Studies in Computational Intelligence, vol. 465. Springer, Berlin (2013)

    Chapter  Google Scholar 

  8. Przybylek, M.R.: Process mining through tree automata. In: International Conference on Evolutionary Computation Theory and Applications (2013)

    Google Scholar 

  9. Rechenberg, I.: Evolutions strategie–optimierung technischer systeme nach prinzipien der biologischen evolution. Ph.D. thesis (1971) [Reprinted by Fromman-Holzboog, 1973]

    Google Scholar 

  10. Ren, C., Wen, L., Dong, J., Ding, H., Wang, W., Qiu, M.: A novel approach for process mining based on event types. In: IEEE SCC 2007, pp. 721–722 (2007)

    Google Scholar 

  11. Valiant, L.: A theory of the learnable. In: Communications of The ACM, vol. 27 (1984)

    Article  Google Scholar 

  12. van der Aalst, W.: Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer, Berlin (2011)

    Google Scholar 

  13. van der Aalst, W., de Medeiros, A.A., Weijters, A.: Process equivalence in the context of genetic mining. BPM Center Report BPM-06-15. www.BPMcenter.org (2006)

  14. van der Aalst, W., Pesic, M.S.M.: Beyond process mining: from the past to present and future. BPM Center Report BPM-09-18. www.BPMcenter.org (2009)

  15. van der Aalst, W., ter Hofstede, A., Kiepuszewski, B., Barros, A.: Workflow patterns. BPM Center Report BPM-00-02. www.BPMcenter.org (2000)

  16. van der Aalst, W., van Dongen, B.: Discovering workflow performance models from timed logs. In: Engineering and Deployment of Cooperative Information Systems, pp. 107–110 (2002)

    Google Scholar 

  17. van der Aalst, W., Weijters, A., Maruster, L.: Workflow mining: discovering process models from event logs. In: BPM Center Report BPM-04-06. www.BPMcenter.org (2006)

  18. Weijters, A., van der Aalst, W.: Process mining: discovering workflow models from event-based data. In: Proceedings of the 13th Belgium-Netherlands Conference on Artificial Intelligence, pp. 283–290, Maastricht. Springer (2001)

    Google Scholar 

  19. Wen, L., Wang, J., Sun, J.: Detecting Implicit Dependencies Between Tasks from Event Logs. Lecture Notes in Computer Science, vol. 3841, pp. 591–603 (2006)

    Chapter  Google Scholar 

  20. Wynn, M., Edmond, D., van der Aalst, W., ter Hofstede, A.: Achieving a general, formal and decidable approach to the or-join in workflow using reset nets. BPM Center Report BPM-04-05. www.BPMcenter.org (2004)

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Author information

Authors and Affiliations

  1. Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland

    Michal R. Przybylek

Authors
  1. Michal R. Przybylek
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Correspondence to Michal R. Przybylek .

Editor information

Editors and Affiliations

  1. Images, Signals and Intelligence Systems Laboratory, University PARIS-EST Creteil (UPEC), Créteil, France

    Kurosh Madani

  2. Departamento de Engenharia Informatica Polo II - Pinhal de Marrocos, University of Coimbra, Coimbra, Portugal

    António Dourado

  3. aSEEB-ISR-IST Av. Rovisco Pais, 1, Technical University of Lisbon (IST), Lisbon, Portugal

    Agostinho Rosa

  4. Rua do Vale de Chaves, Estefanilha, Polytechnic Institute of Setúbal / INSTICC, Setúbal, Portugal

    Joaquim Filipe

  5. Polish Academy of Sciences, Systems Research Institute, Warsaw, Poland

    Janusz Kacprzyk

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Przybylek, M.R. (2016). Tree Automata Mining. In: Madani, K., Dourado, A., Rosa, A., Filipe, J., Kacprzyk, J. (eds) Computational Intelligence. IJCCI 2013. Studies in Computational Intelligence, vol 613. Springer, Cham. https://doi.org/10.1007/978-3-319-23392-5_8

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  • DOI: https://doi.org/10.1007/978-3-319-23392-5_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23391-8

  • Online ISBN: 978-3-319-23392-5

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