TY - GEN
T1 - Comprehensive Process Drift Analysis with the Visual Drift Detection Tool
AU - Yeshchenko, Anton
AU - Di Ciccio, Claudio
AU - Mendling, Jan
AU - Polyvyanyy, Artem
PY - 2019/11
Y1 - 2019/11
N2 - 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.
AB - 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.
M3 - Conference contribution
VL - 2469
T3 - CEUR Workshop Proceedings
SP - 108
EP - 112
BT - Proceedings of the ER Forum and Poster Demos Session 2019 on Publishing Papers with CEUR-WS co-located with 38th International Conference on Conceptual Modeling (ER 2019), Salvador, Brazil, November 4, 2019
A2 - Panach, José Ignacio
A2 - Guizzardi, Renata S.S.
A2 - Claro, Daniela Barreiro
PB - CEUR WS
ER -