VDD: A visual drift detection system for process mining
AuthorYeshchenko, A; Mendling, J; Di Ciccio, C; Polyvyanyy, A
Source TitleCEUR Workshop Proceedings
PublisherCEUR Workshop Proceedings
University of Melbourne Author/sPolyvyanyy, Artem
AffiliationComputing and Information Systems
Document TypeConference Paper
CitationsYeshchenko, A., Mendling, J., Di Ciccio, C. & Polyvyanyy, A. (2020). VDD: A visual drift detection system for process mining. Proceedings of the ICPM Doctoral Consortium and Tool Demonstration Track 2020 co-located with the 2nd International Conference on Process Mining (ICPM 2020), 2703, pp.31-34. CEUR Workshop Proceedings.
Access StatusOpen Access
Open Access URLPublished version
ARC Grant codeARC/DP180102839
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.
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