For various applications such as workflow discovering and clustering, it is necessary to measure the distance between two process models. In this paper, a quantitative measure was proposed to calculate the distance or similarity between different structured processes. The authors firstly introduced a structured workflow model and transformed each process into a process structure tree, and then calculated the process distance and its similarity based on the tree edit distance of two structure trees. The proposed distance metric satisfied three distance measure properties, i. e., identity of indiscernibility, symmetry and triangle inequality. These properties enabled the distance metric to be a quantitative tool in effective process model management activities. The experimental studies show that the method is feasible. Compared to the adjacency matrix method, the proposed method is more reasonable since it takes the semantic distance between different structures into consideration.%在工作流的发现和聚类等应用中,需要对两个工作流模型的距离进行度量.因此,提出一种计算两个不同结构化工作流的距离定量度量方法.首先介绍了结构化工作流,并将每一个结构化工作流转换为流程结构树;然后基于两个结构树之间的树编辑距离来计算工作流之间的距离及相应相似度.该距离度量方法满足距离度量的3个属性,即同实体不可区分性、对称性和三角不等式性质.这些属性使得该距离度量方法可以在工作流模型管理活动中作为定量分析工具.实验结果表明,基于树编辑距离的工作流度量方法是可行的.同时,与基于邻接矩阵的距离度量方法相比,该方法考虑了不同结构之间的语义距离,有效验证了此方法的合理性.
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