Mining Process Models with Duplicate Tasks from Workflow Logs
نویسندگان
چکیده
Current workflow management systems (WFMS) require user to provide explicit process models. The design of model is a difficult, costly and error-prone task. This presents a practical barrier to the adoption of workflow management technologies. A possible solution is process mining which can distill workflow models from a set of real executions. However, the present research in process mining still meets many challenges. The problem of duplicate tasks is one of them, which refers to the situation that the same task can appear multiple times in one workflow model. The -algorithm is proved to mine sound Structured Workflow nets without task duplication. Combining techniques of machine leaning and the -algorithm, a new algorithm called * that can deal with duplicate tasks is proposed and has been implemented in a research prototype. In nine scenarios, the *-algorithm is evaluated experimentally to show its validity.
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