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X-Processes: Process model discovery with the best balance among fitness, precision, simplicity, and generalization through a genetic algorithm

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Autor(es):
Fantinato, Marcelo ; Peres, Sarajane Marques ; Reijers, Hajo A.
Número total de Autores: 3
Tipo de documento: Artigo Científico
Fonte: INFORMATION SYSTEMS; v. 119, p. 25-pg., 2023-07-10.
Resumo

Although process model discovery has been largely investigated over the past two decades, existing process discovery methods are not yet considered fully satisfactory. A particular issue is the difficulty of discovering process models with a good balance among recall (or fitness), precision, generalization, and simplicity, notably for real-world event logs. This article revisits the genetic algorithms-based X-Processes process discovery method, discussing the results of using a fitness function calculated through a harmonic mean that considers the four main metrics of process model quality used in process mining - recall, precision, generalization and simplicity. Although genetic algorithms have been used to discover process models, such methods have limitations, as do other non-genetic algorithm-based methods. X-Processes was tested with two harmonic mean options - one based on recall and precision only and another based on the four quality metrics. X-Processes showed superior effectiveness when compared to state-of-the-art process discovery methods, including one also based on genetic algorithms. The experimental results obtained for both harmonic mean options, using 12 real-world event logs, show that the overall quality of all process models discovered by X-Processes is superior to that of the baseline methods. While its execution time is longer than the other compared process discovery methods, X-Processes emerges as a solution when the need for a higher quality process model outweighs the hunger for agility. & COPY; 2023 Elsevier Ltd. All rights reserved. (AU)

Processo FAPESP: 20/05248-4 - Aprimoramento do algoritmo X-Processes para descobrir modelos de processo mais precisos
Beneficiário:Marcelo Fantinato
Modalidade de apoio: Auxílio à Pesquisa - Regular
Processo FAPESP: 17/26491-1 - Uma abordagem evolutiva para a descoberta de processos de negócio não estruturados com base em coevolução cooperativa e no modelo de ilha
Beneficiário:Marcelo Fantinato
Modalidade de apoio: Bolsas no Exterior - Pesquisa