Mining Process Models from Workflow Logs
EDBT '98 Proceedings of the 6th International Conference on Extending Database Technology: Advances in Database Technology
Workflow mining: a survey of issues and approaches
Data & Knowledge Engineering
Computers in Industry - Special issue: Process/workflow mining
Mining exact models of concurrent workflows
Computers in Industry - Special issue: Process/workflow mining
Discovering workflow models from activities' lifespans
Computers in Industry - Special issue: Process/workflow mining
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
BPM'06 Proceedings of the 4th international conference on Business Process Management
Mining workflow recovery from event based logs
BPM'05 Proceedings of the 3rd international conference on Business Process Management
An analysis and taxonomy of unstructured workflows
BPM'05 Proceedings of the 3rd international conference on Business Process Management
ICATPN'05 Proceedings of the 26th international conference on Applications and Theory of Petri Nets
An initial approach to mining multiple perspectives of a business process
The Fifth Richard Tapia Celebration of Diversity in Computing Conference: Intellect, Initiatives, Insight, and Innovations
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Workflow Management Systems help to execute, monitor and manage work process flow and execution. These systems, as they are executing, keep a record of who does what and when (e.g. log of events). The activity of using computer software to examine these records, and deriving various structural data results is called workflow mining. The workflow mining activity, in general, needs to encompass behavioral (process/control-flow), social, informational (data-flow), and organizational perspectives; as well as other perspectives, because workflow systems are "people systems" that must be designed, deployed, and understood within their social and organizational contexts. In this paper, we especially focus on the behavioral perspective of a structured workflow model that preserves the proper nesting and the matched pair properties. That is, this paper proposes an ICN-based mining algorithm that rediscovers a structured workflow process model. We name it σ-Algorithm, because it is incrementally amalgamating a series of temporal workcases (workflow traces) according to three types of basic merging principles conceived in this paper. Where, a temporal workcase is a temporally ordered set of activity execution event logs. We also gives an example to show that how the algorithm works with the temporal workcases.