Associate Professor
Technical University of Denmark
Nowadays, organizational information systems are able to collect high volumes of data in event logs every day. Through process mining techniques, it is possible to extract information from such logs to support organizations in checking process conformance, detecting bottlenecks, and carrying on performance analysis. However, to analyze such “big data” through process mining, events coming from process executions (in the form of event streams) must be processed on-the-fly as they occur. The work presented in this paper is built on top of a technique for the online discovery of declarative process models presented in our previous work. In particular, we introduce a tool providing a dynamic visualization of the models discovered over time showing, as a “process movie”, the sequence of valid business rules at any point in time based on the information retrieved from an event stream. The effectiveness of the visualizer is validated through an event stream pertaining to health insurance claims handling in a travel agency.
In Proceedings of the 3rd International Workshop on Theory and Applications of Process Visualization (TAProViz 2014); Haifa, Israel; 8 September 2014.
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