Abstract
Process mining is a discipline that aims at discovering, monitoring and improving real-life processes by extracting knowledge from event logs. Process discovery and conformance checking are the two main process mining tasks. Process discovery techniques can be used to learn a process model from example traces in an event log, whereas the goal of conformance checking is to compare the observed behavior in the event log with the modeled behavior. In this paper, we propose an approach based on temporal logic query checking, which is in the middle between process discovery and conformance checking. It can be used to discover those LTL-based business rules that are valid in the log, by checking against the log a (user-defined) class of rules. The proposed approach is not limited to provide a boolean answer about the validity of a business rule in the log, but it rather provides valuable diagnostics in terms of traces in which the rule is satisfied (witnesses) and traces in which the rule is violated (counterexamples). We have implemented our approach as a proof of concept and conducted a wide experimentation using both synthetic and real-life logs.
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Räim, M., Di Ciccio, C., Maggi, F.M., Mecella, M., Mendling, J. (2014). Log-Based Understanding of Business Processes through Temporal Logic Query Checking. In: Meersman, R., et al. On the Move to Meaningful Internet Systems: OTM 2014 Conferences. OTM 2014. Lecture Notes in Computer Science, vol 8841. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45563-0_5
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