VDD: A Visual Drift Detection System for Process Mining

Yeshchenko, Anton and Mendling, Jan and Di Ciccio, Claudio ORCID: https://orcid.org/0000-0001-5570-0475 and Polyvyanny, Artem (2020) VDD: A Visual Drift Detection System for Process Mining. In: CEUR Workshop Proceedings. pp. 31-34.

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Abstract

Research on concept drift detection has inspired recent advancements of process mining and expanding the growing arsenal of process analysis tools. What has so far been missing in this new research stream are techniques that support comprehensive process drift analysis in terms of localizing, drillingdown, quantifying, and visualizing process drifts. In our research, we built on ideas from concept drift, process mining, and visualization research and present a novel web-based software tool to analyze process drifts, called Visual Drift Detection (VDD). Addressing the comprehensive analysis requirements, our tool is of benefit to researchers and practitioners in the business intelligence and process analytics area. It constitutes a valuable aid to those who are involved in business process redesign projects.

Item Type:	Book Section
Additional Information:	This work is partially funded by the EU H2020 program under MSCA-RISE agreement 645751 (RISEBPM). Artem Polyvyanyy is partly supported by the Australian Research Council Discovery Project DP180102839. Claudio Di Cicciois partly supported by the MIUR under grant "Dipartimentidi eccellenza 2018-2022" of the Department of Computer Science of Sapienza University of Rome.
Divisions:	Departments > Wirtschaftsinformatik u. Operations Mgmt > Data, Process and Knowledge Management > Mendling
Version of the Document:	Published
Depositing User:	Gertraud Novotny
Date Deposited:	24 Mar 2021 15:11
Last Modified:	25 Mar 2021 08:27
Related URLs:	http://pm4py.org
FIDES Link:	https://bach.wu.ac.at/d/research/results/99082/
URI:	https://epub.wu.ac.at/id/eprint/8056

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