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Erschienen in:
2012 | OriginalPaper | Buchkapitel
Discovering Workflow Changes with Time-Based Trace Clustering
verfasst von : Rafael Accorsi, Thomas Stocker
Erschienen in: Data-Driven Process Discovery and Analysis
Verlag: Springer Berlin Heidelberg
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This paper proposes a trace clustering approach to support process discovery of configurable, evolving process models. The clustering approach allows auditors to distinguish between different process variants within a timeframe, thereby visualizing the process evolution. The main insight to cluster entries is the “distance” between activities, i.e. the number of steps between an activity pair. By observing non-transient modifications on the distance, changes in the original process shape can be inferred and the entries clustered accordingly. The paper presents the corresponding algorithms and exemplifies its usage in a running example.