Contemporary workflow management systems are driven by explicit process models, i.e., a completely specified workflow design is required in order to enact a given workflow process. Creating a workflow design is a complicated time-consuming process and typically there are discrepancies between the actual workflow processes and the processes as perceived by the management. Therefore, new techniques for discovering workflow models have been required. Starting point for such techniques are so-called &ldquo / workflow logs" / containing information about the workflow process as it is actually being executed. In this thesis, new mining technique based on time information is proposed. It is assumed that events in workflow logs bear timestamps. This information is used in to determine task orders and control flows between tasks. With this new algorithm, basic workflow structures, sequential, parallel, alternative and iterative (i.e., loops) routing, and advance workflow structure or-join can be mined. While mining the workflow structures, this algorithm also handles the noise problem.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12606149/index.pdf |
| Date | 01 May 2005 |
| Creators | Canturk, Deniz |
| Contributors | Kesim Cicekli, Nihan |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
Page generated in 0.0017 seconds