Facing the increasing global competition, modern business organizations have to respond quickly and correctly to the constant changing environment to ensure their competitive advantages. This goal has led to a recent surge of work on Business Process Reengineering (BPR) and Workflow Management. While most work in these areas assume that process definitions are known in a priori, it is widely recognized that defining a process type which totally represents all properties of the underlying business process is a difficult job. This job is currently practiced in a very ad-hoc fashion. In this paper, we postulate an algorithm to discover the process definition from analyzing the existing process instances. We compare our algorithm with other existing algorithms proposed in the literature in terms of time complexity and apply these algorithms through synthetic data sets to measure the qualities of output results. It has been found that our algorithm is able to return the process definitions closer to the real ones in a faster manner.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0523100-143315 |
| Date | 23 May 2000 |
| Creators | Yang, Wan-Shiou |
| Contributors | San-Yia Hwang, Chia-Mai Chen, Chih-Ping Wei |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0523100-143315 |
| Rights | unrestricted, Copyright information available at source archive |
Page generated in 0.0022 seconds