Abstract
Workflow management systems (WfMS) are widely used by business enterprises as tools for administrating, automating and scheduling the business process activities with the available resources. Since the control flow specifications of workflows are manually designed, they entail assumptions and errors, leading to inaccurate workflow models. Decision points, the XOR nodes in a workflow graph model, determine the path chosen toward completion of any process invocation. In this work, we show that positioning the decision points at their earliest points can improve process efficiency by decreasing their uncertainties and identifying redundant activities. We present novel techniques to discover the earliest positions by analyzing workflow logs and to transform the model graph. The experimental results show that the transformed model is more efficient with respect to its average execution time and uncertainty, when compared to the original model.
Original language | English |
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Pages (from-to) | 1037-1055 |
Number of pages | 19 |
Journal | Information Systems |
Volume | 32 |
Issue number | 7 |
DOIs | |
Publication status | Published - Nov 2007 |
Externally published | Yes |
Keywords
- Classification
- Process mining
- Workflow graph models
ASJC Scopus subject areas
- Software
- Information Systems
- Hardware and Architecture