Conference Proceedings

Comprehensive Process Drift Detection with Visual Analytics

Anton Yeshchenko, Claudio Di Ciccio, Jan Mendling, Artem Polyvyanyy

38th International Conference, ER 2019 | Springer | Published : 2019

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 paper, we propose a novel technique for managing process drifts, called Visual Drift Detection (VDD), which fulfills these requirements. The technique starts by clustering declarative process constraints discovered from recorded logs of executed business processes based on their similarity and then applies change point detection on the identified clusters to detect drifts. VDD complements these features with detail..

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