Clustering Traces using Sequence Alignment

Joerg Evermann, Tom Thaler, Peter Fettke

In: Proceedings of the 11th International Workshop on Business Process Intelligence,. International Workshop on Business Process Intelligence (BPI-15) befindet sich International Conference on Business Process Management July 31-August 3 Innsbruck Austria 2015.


Process mining discovers process models from even logs. Logs containing heterogeneous sets of traces can lead to complex process models that try to account for very different behaviour in a single model. Trace clustering identifes homogeneous sets of traces within a heterogeneous log and allows for the discovery of multiple, simpler process models. In this paper, we present a trace clustering method based on local alignment of sequences, subsequent multidimensional scaling, and k-means clustering. We describe its implementation and show that its performance compares favourably to state-of-the-art clustering approaches on two evaluation problems.

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence