Yeshchenko, Anton ORCID: https://orcid.org/0000-0002-5346-8358 and Di Ciccio, Claudio
ORCID: https://orcid.org/0000-0001-5570-0475 and Mendling, Jan
ORCID: https://orcid.org/0000-0002-7260-524X and Polyvyanyy, Artem
ORCID: https://orcid.org/0000-0002-7672-1643
(2019)
Comprehensive Process Drift Analysis with the Visual Drift Detection Tool.
In:
Proceedings of the ER Forum and Poster & Demos Session 2019.
2469,
CEUR Workshop Proceedings, Salvador, Brazil.
pp. 108-112.
ISBN 1613-0073
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Text
ERDemo01.pdf Available under License Creative Commons: Attribution 4.0 International (CC BY 4.0). Download (662kB) | Preview |
Abstract
Recent research has introduced ideas from concept drift into process mining to enable the analysis of changes in business processes over time. This stream of research, however, has not yet addressed the challenges of drift categorization, drilling-down, and quantification. In this tool demonstration paper, we present a novel software tool to analyze process drifts, called Visual Drift Detection (VDD), which fulfills these requirements. The tool is of benefit to the researchers and practitioners in the business intelligence and process analytics area, and can constitute a valuable aid to those who are involved in business process redesign endeavors.
Item Type: | Book Section |
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Additional Information: | This work is partially funded by the EU H2020 program under MSCA-RISE agreement 645751 (RISE BPM). Artem Polyvyanyy was partly supported by the Australian Research Council Discovery Project DP180102839. |
Keywords: | Process mining, Time series Analysis, Change point detection, Declarative process models |
Divisions: | Departments > Informationsverarbeitung u Prozessmanag. > Informationswirtschaft > Mendling |
Version of the Document: | Published |
Depositing User: | Gertraud Novotny |
Date Deposited: | 29 Nov 2019 09:26 |
Last Modified: | 29 Nov 2019 09:26 |
Related URLs: | |
FIDES Link: | https://bach.wu.ac.at/d/research/results/92904/ |
URI: | https://epub.wu.ac.at/id/eprint/7332 |
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