A Block-Structured Mining Approach to Support Process Discovery

Deploying process-driven information systems is a time-consuming and error-prone. Constructing process models from scratch is a complicated time consuming task that often requires high expertise. And there are discrepancies between the actual workflow processes and the processes as perceived by the management. Therefore, techniques for discovering process models have been developed. Process mining just attempts to improve this by automatically generating a process model from sets of systems´ executions (audit logs). In this paper, a block-structured process mining approach from audit logs to support process discovery is designed. Compare with other algorithms, the result of this approach is more visible and understanding of process model. This approach is used to a widely commercial tool for the visualization and analysis of process model.