PLG: A Framework for the Generation of Business Process Models and Their Execution Logs
Evaluating process mining algorithms would require the availability of a suite of real-world business processes and their execution logs, which hardly are available. In this paper we propose an approach for the random generation of business processes and their execution logs. The proposed approach is based on the generation of process descriptions via a stochastic context-free grammar whose definition is based on well-known process patterns. An algorithm for the generation of execution instances is also proposed. The implemented tools are publicly available.
Keywordsprocess mining business processes log generation Petri net benchmark dataset
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