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In order to identify business processes effectively, historical data, such as event log, can be used as a base to retrieve abstract process model. The result of process mining can provide necessary information to deploy process-aware information systems. Process structure patterns disclosing the relationship among activities is one of the most important aspects. To retrieve the process model comprehensively and quickly, this paper propose a simulated annealing process mining approach to address this issue. Main contribution of the work includes : (1) Apply the simulated annealing approach under the setting of process mining. (2)Represent events as "causal matrix". (3) Evaluate the mining result with a quantitative measurement, incorporate the ideas above into existing simulated annealing algorithm to form an integrated solution. We give experimental results which created by the ProM, a platform for business process mining, with the data it provides.
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Stored only when both papers are in the corpus — 21 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.