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The Drift Analysis in the Process Mining with the Visual Drift Detection Tool
Anton Yeshchenko, Claudio Di Ciccio, Jan Mendling, Artem Polyvyanyy
Vienna University of Economics and Business, Vienna, Austria, The University of Melbourne, Parkville, VIC, 3010, Australia
Abstract: The business process models change in the recent past to where the shift from concept drift into process mining occurs over a period of time. The studies conducted till now have not addressed the requirements and not yet addressed the challenges of drift categorization, drilling-down, and quantification. Throughout this work, we present a new 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.
Keywords: Drift Detection, Process Mining, Time Series Analysis, Change Point Detection, Declarative Process Models The Drift Analysis in the Process Mining with the Visual Drift Detection Tool
DOI:https://doi.org/10.6025/ed/2020/9/1/24-28
Full_Text   PDF 1.02 MB   Download:   95  times
References:

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