AS-SIM: An Approach to Action-State Process Model Discovery

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Process model discovery has gained a lot of attention in recent years, to mine a process model from traces of process executions. In our recent work, we have proposed SIM (Semantic Interactive Miner), an innovative process mining tool able to discover the process model in an incremental way: first, a mining module builds an initial process model, called log-tree, from the available traces; then, such a model is refined interactively with domain experts, through merge and abstraction operations. However, in several contexts, traces are richer: they do not record only actions, but also states (i.e., values of parameters possibly affected by the actions). A typical example is the medical domain, where traces contain both actions and measurements of patients’ parameters. In this paper, we propose AS-SIM (Action-State SIM), the first approach aiming at discovering a comprehensive model, in which two distinct classes of nodes are considered, to capture both actions and states. We focus on the definition and on the discovery of the initial action-state process model (called action-state log-tree), while in our future work we will extend SIM’s merge and abstraction operations accordingly.

Original languageEnglish
Title of host publicationFoundations of Intelligent Systems - 26th International Symposium, ISMIS 2022, Proceedings
EditorsMichelangelo Ceci, Sergio Flesca, Elio Masciari, Giuseppe Manco, Zbigniew W. Raś, Zbigniew W. Raś
PublisherSpringer Science and Business Media Deutschland GmbH
Pages336-345
Number of pages10
ISBN (Print)9783031165634
DOIs
Publication statusPublished - 2022
Event26th International Symposium on Methodologies for Intelligent Systems, ISMIS 2022 - Rende, Italy
Duration: 3 Oct 20225 Oct 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13515 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference26th International Symposium on Methodologies for Intelligent Systems, ISMIS 2022
Country/TerritoryItaly
CityRende
Period3/10/225/10/22

Keywords

  • Mining action+state evolution
  • Process mining
  • Process model discovery

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