Visual Analytics in Process Mining: Classification of Process Mining Techniques

Simone Kriglstein, Margit Pohl, Stefanie Rinderle-Ma, Magdalena Stallinger

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

The increasing interest from industry and academia has driven the development of process mining techniques over the last years. Since the process mining entails a strong explorative perspective, the combination of process mining and visual analytics methods is a fruitful multidisciplinary solution to enable the exploration and the understanding of large amounts of event log data. In this paper, we propose a first approach how process mining techniques can be categorized with respect to visual analytics aspects. Since ProM is a widely used open-source framework which includes most of the existing process mining techniques as plug-ins, we concentrate on the plugins of ProM as use case to show the applicability of our approach.

Original languageEnglish
Title of host publicationEuroVA 2016 - EuroVis Workshop on Visual Analytics
EditorsDieter Fellner
PublisherEurographics Association
Pages43-47
Number of pages5
ISBN (Electronic)9783038680161
DOIs
StatePublished - 2016
Externally publishedYes
Event7th International EuroVis Workshop on Visual Analytics, EuroVA 2016 at EuroVis 2016 - Groningen, Netherlands
Duration: 6 Jun 20167 Jun 2016

Publication series

NameInternational Workshop on Visual Analytics
ISSN (Electronic)2664-4487

Conference

Conference7th International EuroVis Workshop on Visual Analytics, EuroVA 2016 at EuroVis 2016
Country/TerritoryNetherlands
CityGroningen
Period6/06/167/06/16

Fingerprint

Dive into the research topics of 'Visual Analytics in Process Mining: Classification of Process Mining Techniques'. Together they form a unique fingerprint.

Cite this