IM-viz: A Tool for the Step-by-step Visualization of the Inductive Miner

Florian Lang, Din Hida, Yingjie Bian, Adrian Rebmann, Han van der Aa

Veröffentlichungen: Beitrag in BuchBeitrag in KonferenzbandPeer Reviewed

Abstract

The Inductive Miner is a state-of-the-art algorithm for process discovery and a staple in process mining education, since its divide-and-conquer nature can teach students how to recognize behavioral relations in event data and to break up a discovery problem into smaller parts. However, a key problem from this educational perspective is that the algorithm’s manual application is time consuming, involving a considerable amount of drawing, whereas existing implementations of the algorithm only show the final outcome, not its intermediary steps. To overcome this, we present IM-viz, an educational process mining tool that visualizes the application of the Inductive Miner and the Inductive Miner infrequent in an iterative manner. IM-viz allows users to interactively explore how inductive mining works and how it deals with different kinds of event data, thus providing a convenient means for process mining students and educators to establish and analyze step-by-step process discovery examples.

OriginalspracheEnglisch
TitelDoctoral Consortium and Demo Track 2023 at the International Conference on Process Mining, ICPM-DCDT 2023
Band3648
PublikationsstatusVeröffentlicht - 2023
VeranstaltungDoctoral Consortium and Demo Track 2023 at the International Conference on Process Mining, ICPM-DCDT 2023 - Rome, Italien
Dauer: 27 Okt. 2023 → …

Publikationsreihe

ReiheCEUR Workshop Proceedings
ISSN1613-0073

Konferenz

KonferenzDoctoral Consortium and Demo Track 2023 at the International Conference on Process Mining, ICPM-DCDT 2023
Land/GebietItalien
OrtRome
Zeitraum27/10/23 → …

ÖFOS 2012

  • 102015 Informationssysteme

Zitationsweisen