A Comparative Analysis of Process Instance Cluster Techniques

The application of process mining and analysis techniques to the process logs of information systems often leads to highly complex results, e.g. in terms of a high number of elements in the mined model. Thus, clustering corresponding log files is mandatory in the context of an expedient analysis. Against that background, many cluster techniques have been developed during the last years but, at the same time, it is unclear how powerful they operate in particular application scenarios. Therefore, the paper at hand aims at analyzing and comparing the capabilities of existing cluster techniques with regard to different objectives. As a result, it is shown that some techniques are more suitable for the handling of particular scenarios than others and there are also general challenges in their application, which should be addressed in future work.