Mining structured Petri nets for the visualization of process behavior
Tipo de documentoTexto en actas de congreso
Fecha de publicación2016
EditorAssociation for Computing Machinery (ACM)
Condiciones de accesoAcceso abierto
Visualization is essential for understanding the models obtained by process mining. Clear and efficient visual representations make the embedded information more accessible and analyzable. This work presents a novel approach for generating process models with structural properties that induce visually friendly layouts. Rather than generating a single model that captures all behaviors, a set of Petri net models is delivered, each one covering a subset of traces of the log. The models are mined by extracting slices of labelled transition systems with specific properties from the complete state space produced by the process logs. In most cases, few Petri nets are sufficient to cover a significant part of the behavior produced by the log.
CitaciónSan Pedro, J. de, Cortadella, J. Mining structured Petri nets for the visualization of process behavior. A: ACM Symposium on Applied Computing. "Proceedings of the 31st ACM Symposium on Applied Computing". Pisa: Association for Computing Machinery (ACM), 2016, p. 839-846.
Versión del editorhttp://dl.acm.org/citation.cfm?doid=2851613.2851645