Visual Analytics in Process Mining: Classification of Process Mining Techniques

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dc.contributor.authorKriglstein, Simoneen_US
dc.contributor.authorPohl, Margiten_US
dc.contributor.authorRinderle-Ma, Stefanieen_US
dc.contributor.authorStallinger, Magdalenaen_US
dc.contributor.editorNatalia Andrienko and Michael Sedlmairen_US
dc.date.accessioned2016-06-09T09:32:10Z
dc.date.available2016-06-09T09:32:10Z
dc.date.issued2016en_US
dc.description.abstractThe 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.en_US
dc.description.sectionheadersTemporal Data Analysisen_US
dc.description.seriesinformationEuroVis Workshop on Visual Analytics (EuroVA)en_US
dc.identifier.doi10.2312/eurova.20161123en_US
dc.identifier.isbn978-3-03868-016-1en_US
dc.identifier.issn-en_US
dc.identifier.pages43-47en_US
dc.identifier.urihttps://doi.org/10.2312/eurova.20161123en_US
dc.identifier.urihttps://diglib.eg.org:443/handle/10
dc.publisherThe Eurographics Associationen_US
dc.subjectH.4.m [Information Systems Applications]en_US
dc.subjectMiscellaneousen_US
dc.titleVisual Analytics in Process Mining: Classification of Process Mining Techniquesen_US
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