A genetic algorithm for discovering process trees

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Existing process discovery approaches have problems dealing with competing quality dimensions (fitness, simplicity, generalization, and precision) and may produce anomalous process models (e.g., deadlocking models). In this paper we propose a new genetic process mining algorithm that discovers process models from event logs. The tree representation ensures the soundness of the model. Moreover, as experiments show, it is possible to balance the different quality dimensions. Our genetic process mining algorithm is the first algorithm where the search process can be guided by preferences of the user while ensuring correctness.
Original languageEnglish
Title of host publicationProceedings of the IEEE Congress on Evolutionary Computation (CEC 2012, Brisbane, Australia, June 10-15, 2012)
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Print)978-1-4673-1510-4
Publication statusPublished - 2012
Eventconference; IEEE Congress on Evolutionary Computation; 2012-06-10; 2012-06-15 -
Duration: 10 Jun 201215 Jun 2012


Conferenceconference; IEEE Congress on Evolutionary Computation; 2012-06-10; 2012-06-15
OtherIEEE Congress on Evolutionary Computation


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