Mining the role-oriented process models based on genetic algorithm

Authors:
Weidong Zhao;Qinhe Lin;Yue Shi;Xiaochun Fang
Affiliations:
Software School, Fudan University, Shanghai, China;Software School, Fudan University, Shanghai, China;Software School, Fudan University, Shanghai, China;Software School, Fudan University, Shanghai, China
Venue:
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
Year:
2012

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Abstract

Traditional role-oriented process modeling seems to be subjective in identifying roles. To solve the problem, the similarity of activities is used in this paper. Sub-processes with high similarity are recognized as the process undertaken by a certain role. In this way, a relatively objective role identification approach is proposed, which determines the interaction between roles and establishes the role-activity diagram. Furthermore, by analyzing the interaction between roles, genetic algorithm is used to introduce multiple factors to optimize the identification. Therefore, an optimized role-oriented process modeling approach is established and an example is presented to show the feasibility of this approach.