I-PALIA: Discovering BPMN Processes with Duplicated Activities for Healthcare Domains

Carlos Fernandez-Llatas*, Andrea Burattin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Process mining encompasses a range of methods designed to analyze event logs. Among these methods, control-flow discovery algorithms are particularly significant, as they enable the identification of real-world process models, known as in-vivo processes, in contrast to anticipated models. An obstacle faced by control-flow discovery algorithms is their limited ability to recognize duplicated activities, which are activities that occur in multiple locations within a process. This issue is particularly relevant in the healthcare sector, where numerous instances of duplicated activities exist in processes but remain undetected by conventional algorithms. This article introduces a novel concept for a control-flow discovery algorithm capable of effectively revealing duplicated activities. The effectiveness of this technique is demonstrated through experimentation on a synthetic dataset. Moreover, the algorithm has been implemented and its source code is available as open-source software, accessible both as a ProM plugin and a Java Maven dependency.
Original languageEnglish
Title of host publicationProceedings of the 5th International Conference on Process Mining (ICPM 2023)
Volume503
PublisherSpringer
Publication date2024
Pages247–258
ISBN (Print)978-3-031-56106-1
ISBN (Electronic)978-3-031-56107-8
DOIs
Publication statusPublished - 2024
Event5th International Conference on Process Mining - Rome, Italy
Duration: 23 Oct 202327 Oct 2023
Conference number: 5

Conference

Conference5th International Conference on Process Mining
Number5
Country/TerritoryItaly
CityRome
Period23/10/202327/10/2023

Keywords

  • Process mining
  • Control-flow discovery
  • BPMN
  • Duplicated activities

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