Wednesday, October 14, 2009

IEEE Task Force on Process Mining

IEEE Task Force on Process Mining Established More and more people, both in industry and academia, consider process mining as one of the most important innovations in the field of business process management. It joins ideas of process modeling and analysis on the one hand and data mining and machine learning on the other. Therefore, the IEEE has established a Task Force on Process Mining. This Task Force is established in the context of the Data Mining Technical Committee (DMTC) of the Computational Intelligence Society (CIS) of the Institute of Electrical and Electronic Engineers, Inc. (IEEE). The chair is prof. Wil van der Aalst (www.vdaalst.com). The goal of this Task Force is to promote the research, development, education and understanding of process mining. More concretely, the goal is to: * make end-users, developers, consultants, and researchers aware of the state-of-the-art in process mining, * promote the use of process mining techniques and tools and stimulating new applications, * play a role in standardization efforts for logging event data, * the organization of tutorials, special sessions, workshops, panels, * the organization of Conferences/Workshop with IEEE CIS Technical Co-Sponsorship, and * publications in the form of special issues in journals, books, articles (e.g., in the IEEE Computational Intelligence Magazine). Note that process mining includes (automated) process discovery (extracting process models from an event log), conformance checking (monitoring deviations by comparing model and log), social network/organizational mining, automated construction of simulation models, case prediction, and history-based recommendations. See the initial website http://www.win.tue.nl/ieeetfpm/ for information and the current list of members of this task force (more information will follow). Feel free to contact these members if you have requests or ideas related to the promotion of process mining. Wil van der Aalst Chair of the IEEE Task Force on Process Mining

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