The mining of workflow models from workflow logs is an alternative to construct models from scratch. It also offers a mean to analyze and optimize workflows already supported by workflow management systems. In many cases, the benefit of workflow mining depends on the exactness of the mined models. T
Discovering models of behavior for concurrent workflows
โ Scribed by Jonathan E. Cook; Zhidian Du; Chongbing Liu; Alexander L. Wolf
- Book ID
- 104015473
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 334 KB
- Volume
- 53
- Category
- Article
- ISSN
- 0166-3615
No coin nor oath required. For personal study only.
โฆ Synopsis
Understanding the dynamic behavior of a workflow is crucial for being able to modify, maintain, and improve it. A particularly difficult aspect of some behavior is concurrency. Automated techniques which seek to mine workflow data logs to discover information about the workflows must be able to handle the concurrency that manifests itself in the workflow executions. This paper presents techniques to discover patterns of concurrent behavior from traces of workflow events. The techniques are based on a probabilistic analysis of the event traces. Using metrics for the number, frequency, and regularity of event occurrences, a determination is made of the likely concurrent behavior being manifested by the system. Discovering this behavior can help a workflow designer better understand and improve the work processes they are managing.
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