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Title: |
Discovering Workflow Changes with Time-based Trace Clustering |
Publication type: |
Conference papers |
Authors: |
Accorsi R, Stocker T
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Year of publication: |
2012 |
Journal: |
Post-proceedings of the IFIP Symposium on Data-Driven Process Discovery and Analysis |
Pages: |
154 - 168 |
Series: |
Lecture Notes in Business Information Processing, #116 |
Abstract: |
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. |
URL/DOI: |
http://dx.doi.org/10.1007/978-3-642-34044-4
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PDF: |
http://files.telematik.un[...]tions/simpda11-pp.pdf
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