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Process Mining Put into Context
January/February 2012 (vol. 16 no. 1)
pp. 82-86
Wil M.P. van der Aalst, Eindhoven University of Technology
Schahram Dustdar, Technical University of Vienna

Process mining techniques help organizations discover and analyze business processes based on raw event data. The recently released "Process Mining Manifesto" presents guiding principles and challenges for process mining. Here, the authors summarize the manifesto's main points and argue that analysts should take into account the context in which events occur when analyzing processes.

1. W.M.P. van der Aalst, Process Mining: Discovery, Conformance, and Enhancement of Business Processes, Springer, 2011.
2. IEEE Task Force on Process Mining, "Process Mining Manifesto," Proc. Business Process Mining Workshops, Lecture Notes in Business Information Processing, Springer, 2011.
3. W.M.P. van der Aalst, A.J.M.M. Weijters, and L. Maruster, "Workflow Mining: Discovering Process Models from Event Logs," IEEE Trans. Knowledge and Data Eng., vol. 16, no. 9, 2004, pp. 1128–1142.
4. R.P. Jagadeesh Chandra Bose et al., "Handling Concept Drift in Process Mining," Proc. Int'l Conf. Advanced Information Systems Eng. (CAiSE 11), LNCS 6741, Springer, 2011, pp. 391–405.
5. K. Ploesser et al., "Learning from Context to Improve Business Processes," BPTrends, Jan. 2009, pp. 1–7.
6. M. Rosemann, J. Recker, and C. Flender, "Contextualization of Business Processes," Int'l J. Business Process Integration and Management, vol. 3, no. 1, 2008, pp. 47–60.
1. W.M.P. van der Aalst, "Business Process Simulation Revisited," Enterprise and Organizational Modeling and Simulation, Lecture Notes in Business Information Processing, vol. 63, J. Barjis ed., Springer, 2010, pp. 1–14.

Index Terms:
process mining, business intelligence, business process management
Citation:
Wil M.P. van der Aalst, Schahram Dustdar, "Process Mining Put into Context," IEEE Internet Computing, vol. 16, no. 1, pp. 82-86, Jan.-Feb. 2012, doi:10.1109/MIC.2012.12
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