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Towards Action-State Process Model Discovery

Author

Listed:
  • Alessio Bottrighi

    (Department of Science, Technology and Innovation, Università del Piemonte Orientale, Viale Teresa Michel 11, 15121 Alessandria, Italy
    Laboratorio Integrato di Intelligenza Artificiale e Informatica Medica DAIRI, Azienda Ospedaliera SS. Antonio e Biagio e Cesare Arrigo, Alessandria e DISIT—Università del Piemonte Orientale, 15121 Alessandria, Italy
    These authors contributed equally to this work.)

  • Marco Guazzone

    (Department of Science, Technology and Innovation, Università del Piemonte Orientale, Viale Teresa Michel 11, 15121 Alessandria, Italy
    Consorzio Nazionale Interuniversitario per le Telecomunicazioni (CNIT), 43124 Parma, Italy
    These authors contributed equally to this work.)

  • Giorgio Leonardi

    (Department of Science, Technology and Innovation, Università del Piemonte Orientale, Viale Teresa Michel 11, 15121 Alessandria, Italy
    Laboratorio Integrato di Intelligenza Artificiale e Informatica Medica DAIRI, Azienda Ospedaliera SS. Antonio e Biagio e Cesare Arrigo, Alessandria e DISIT—Università del Piemonte Orientale, 15121 Alessandria, Italy
    These authors contributed equally to this work.)

  • Stefania Montani

    (Department of Science, Technology and Innovation, Università del Piemonte Orientale, Viale Teresa Michel 11, 15121 Alessandria, Italy
    Laboratorio Integrato di Intelligenza Artificiale e Informatica Medica DAIRI, Azienda Ospedaliera SS. Antonio e Biagio e Cesare Arrigo, Alessandria e DISIT—Università del Piemonte Orientale, 15121 Alessandria, Italy
    These authors contributed equally to this work.)

  • Manuel Striani

    (Department of Science, Technology and Innovation, Università del Piemonte Orientale, Viale Teresa Michel 11, 15121 Alessandria, Italy
    Laboratorio Integrato di Intelligenza Artificiale e Informatica Medica DAIRI, Azienda Ospedaliera SS. Antonio e Biagio e Cesare Arrigo, Alessandria e DISIT—Università del Piemonte Orientale, 15121 Alessandria, Italy
    These authors contributed equally to this work.)

  • Paolo Terenziani

    (Department of Science, Technology and Innovation, Università del Piemonte Orientale, Viale Teresa Michel 11, 15121 Alessandria, Italy
    Laboratorio Integrato di Intelligenza Artificiale e Informatica Medica DAIRI, Azienda Ospedaliera SS. Antonio e Biagio e Cesare Arrigo, Alessandria e DISIT—Università del Piemonte Orientale, 15121 Alessandria, Italy
    These authors contributed equally to this work.)

Abstract

Process model discovery covers the different methodologies used to mine a process model from traces of process executions, and it has an important role in artificial intelligence research. Current approaches in this area, with a few exceptions, focus on determining a model of the flow of actions only. However, in several contexts, (i) restricting the attention to actions is quite limiting, since the effects of such actions also have to be analyzed, and (ii) traces provide additional pieces of information in the form of states (i.e., values of parameters possibly affected by the actions); for instance, in several medical domains, the traces include both actions and measurements of patient parameters. In this paper, we propose AS-SIM (Action-State SIM), the first approach able to mine a process model that comprehends two distinct classes of nodes, to capture both actions and states.

Suggested Citation

  • Alessio Bottrighi & Marco Guazzone & Giorgio Leonardi & Stefania Montani & Manuel Striani & Paolo Terenziani, 2023. "Towards Action-State Process Model Discovery," Data, MDPI, vol. 8(8), pages 1-22, August.
    • Handle: RePEc:gam:jdataj:v:8:y:2023:i:8:p:130-:d:1213971
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