Visual Analytics in Process Mining: Classification of Process Mining Techniques

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

Visual Analytics in Process Mining: Classification of Process Mining Techniques

Files

043-047.pdf (380.15 KB)

Date

2016

Authors

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

Publisher

The Eurographics Association

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.

        @inproceedings{10.2312:eurova.20161123
,
booktitle = {EuroVis Workshop on Visual Analytics (EuroVA)
},
editor = {Natalia Andrienko and Michael Sedlmair
},
title = {{Visual Analytics in Process Mining: Classification of Process Mining Techniques
}},
author = {Kriglstein, Simone and 
Pohl, Margit and 
Rinderle-Ma, Stefanie and 
Stallinger, Magdalena
},
year = {2016
},
publisher = {The Eurographics Association
},
ISSN = {-
},
ISBN = {978-3-03868-016-1
},
DOI = {10.2312/eurova.20161123
}
}