Genetic Process Mining: Alignment-based Process Model Mutation

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

6 Citaties (Scopus)

Uittreksel

The Evolutionary Tree Miner (ETM) is a genetic process discovery algorithm that enables the user to guide the discovery process based on preferences with respect to four process model quality dimensions: replay fitness, precision, generalization and simplicity. Traditionally, the ETM algorithm uses random creation of process models for the initial population, as well as random mutation and crossover techniques for the evolution of generations. In this paper, we present an approach that improves the performance of the ETM algorithm by enabling it to make guided changes to process models, in order to obtain higher quality models in fewer generations. The two parts of this approach are: (1) creating an initial population of process models with a reasonable quality; (2) using information from the alignment between an event log and a process model to identify quality issues in a given part of a model, and resolving those issues using guided mutation operations.
TaalEngels
TitelBusiness Process Management Workshops (BPM 2014 International Workshops, Eindhoven, The Netherlands, September 7-8, 2014, Revised Papers)
RedacteurenF. Fournier, J. Mendling
Plaats van productieBerlin
UitgeverijSpringer
Pagina's291-303
Aantal pagina's12
ISBN van geprinte versie978-3-319-15894-5
DOI's
StatusGepubliceerd - 2015

Publicatie series

NaamLecture Notes in Business Information Processing
Volume202
ISSN van geprinte versie1865-1348

Vingerafdruk

Miners

Citeer dit

Eck, van, M. L., Buijs, J. C. A. M., & Dongen, van, B. F. (2015). Genetic Process Mining: Alignment-based Process Model Mutation. In F. Fournier, & J. Mendling (editors), Business Process Management Workshops (BPM 2014 International Workshops, Eindhoven, The Netherlands, September 7-8, 2014, Revised Papers) (blz. 291-303). (Lecture Notes in Business Information Processing; Vol. 202). Berlin: Springer. DOI: 10.1007/978-3-319-15895-2_25
Eck, van, M.L. ; Buijs, J.C.A.M. ; Dongen, van, B.F./ Genetic Process Mining: Alignment-based Process Model Mutation. Business Process Management Workshops (BPM 2014 International Workshops, Eindhoven, The Netherlands, September 7-8, 2014, Revised Papers). redacteur / F. Fournier ; J. Mendling. Berlin : Springer, 2015. blz. 291-303 (Lecture Notes in Business Information Processing).
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abstract = "The Evolutionary Tree Miner (ETM) is a genetic process discovery algorithm that enables the user to guide the discovery process based on preferences with respect to four process model quality dimensions: replay fitness, precision, generalization and simplicity. Traditionally, the ETM algorithm uses random creation of process models for the initial population, as well as random mutation and crossover techniques for the evolution of generations. In this paper, we present an approach that improves the performance of the ETM algorithm by enabling it to make guided changes to process models, in order to obtain higher quality models in fewer generations. The two parts of this approach are: (1) creating an initial population of process models with a reasonable quality; (2) using information from the alignment between an event log and a process model to identify quality issues in a given part of a model, and resolving those issues using guided mutation operations.",
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Eck, van, ML, Buijs, JCAM & Dongen, van, BF 2015, Genetic Process Mining: Alignment-based Process Model Mutation. in F Fournier & J Mendling (redactie), Business Process Management Workshops (BPM 2014 International Workshops, Eindhoven, The Netherlands, September 7-8, 2014, Revised Papers). Lecture Notes in Business Information Processing, vol. 202, Springer, Berlin, blz. 291-303. DOI: 10.1007/978-3-319-15895-2_25

Genetic Process Mining: Alignment-based Process Model Mutation. / Eck, van, M.L.; Buijs, J.C.A.M.; Dongen, van, B.F.

Business Process Management Workshops (BPM 2014 International Workshops, Eindhoven, The Netherlands, September 7-8, 2014, Revised Papers). redactie / F. Fournier; J. Mendling. Berlin : Springer, 2015. blz. 291-303 (Lecture Notes in Business Information Processing; Vol. 202).

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

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Eck, van ML, Buijs JCAM, Dongen, van BF. Genetic Process Mining: Alignment-based Process Model Mutation. In Fournier F, Mendling J, redacteurs, Business Process Management Workshops (BPM 2014 International Workshops, Eindhoven, The Netherlands, September 7-8, 2014, Revised Papers). Berlin: Springer. 2015. blz. 291-303. (Lecture Notes in Business Information Processing). Beschikbaar vanaf, DOI: 10.1007/978-3-319-15895-2_25