Decomposing Petri Nets for Process Mining - A Generic Approach-

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Provided by: Eindhoven University of Technology
Topic: Big Data
Format: PDF
The practical relevance of process mining is increasing as more and more event data become available. Process mining techniques aim to discover, monitor and improve real processes by extracting knowledge from event logs. The two most prominent process mining tasks are: process discovery: learning a process model from example behavior recorded in an event log and conformance checking: diagnosing and quantifying discrepancies between observed behavior and modeled behavior. The increasing volume of event data provides both opportunities and challenges for process mining.
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