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Published in:
2008 | OriginalPaper | Chapter
Process Mining as First-Order Classification Learning on Logs with Negative Events
Authors : Stijn Goedertier, David Martens, Bart Baesens, Raf Haesen, Jan Vanthienen
Published in: Business Process Management Workshops
Publisher: Springer Berlin Heidelberg
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Process mining is the automated construction of process models from information system event logs. In this paper we identify three fundamental difficulties related to process mining: the lack of negative information, the presence of history-dependent behavior and the presence of noise. These difficulties can elegantly dealt with when process mining is represented as first-order classification learning on event logs supplemented with negative events. A first set of process discovery experiments indicates the feasibility of this learning technique.