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.

VDD: A Visual Drift Detection System for Process Mining / Yeshchenko, Anton; Mendling, Jan; DI CICCIO, Claudio; Polyvyanyy, Artem. - 2703:(2020), pp. 31-34. (Intervento presentato al convegno Tool Demonstration Track of the 2nd International Conference on Process Mining (ICPM 2020) tenutosi a Padua, Italy).

VDD: A Visual Drift Detection System for Process Mining

Claudio Di Ciccio;
2020

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.
2020
Tool Demonstration Track of the 2nd International Conference on Process Mining (ICPM 2020)
Process mining; Concept drift; Visual analytics; Clustering; Declarative process modelling
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
VDD: A Visual Drift Detection System for Process Mining / Yeshchenko, Anton; Mendling, Jan; DI CICCIO, Claudio; Polyvyanyy, Artem. - 2703:(2020), pp. 31-34. (Intervento presentato al convegno Tool Demonstration Track of the 2nd International Conference on Process Mining (ICPM 2020) tenutosi a Padua, Italy).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1449467
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