Retrieval and clustering for business process monitoring: Results and improvements

Business process monitoring is a set of activities for organizing process instance logs and for highlighting non-compliances and adaptations with respect to the default process schema. Such activities typically serve as the starting point for a-posteriori log analyses. In recent years, we have implemented a tool for supporting business process monitoring, which allows to retrieve traces of process execution similar to the current one. Moreover, it supports an automatic organization of the trace database content through the application of clustering techniques. Retrieval and clustering rely on a distance definition able to take into account temporal information in traces. In this paper, we report on such a tool, and present the newest experimental results. Moreover, we introduce our recent research directions, that aim at improving the tool performances, usability and visibility with respect to the scientific community. Specifically, we propose a methodology for avoiding exhaustive search in the trace database, by identifying promising regions of the search space, in order to reduce computation time. Moreover, we describe how our work is being incorporated as a plug-in in ProM, an open source framework for process mining and process analysis.