Abstract
A method for discovering workflow nets (WFN) with silent transitions from a log of event traces λ is presented. It operates in two stages; in the first one, λ is partitioned into three classes of traces: normal traces, short abnormal traces, and long abnormal traces. In the second stage, the normal traces are processed to build a WFN that may contain transitions of type initialize and finalize; afterwards, this net is refined by adding the transitions of type skip and redo, which are determined from the short abnormal traces and the long abnormal traces respectively. Implementation and tests are presented.
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