业务流程模型抽象中最优子流程数的确定

Determining Optimal Number of Subprocesses in Business Process Model Abstraction

根据业务流程模型的特征,基于笔者前期工作中给出的两个不同约束条件下的受限k-means行为聚类算法,提出确定最优子流程数的方法。基于对流程结构的假设,同时结合行为语义的经验阈值限定,给出了确定子流程数恰当上限值的方法,以达到减少循环次数的目的。根据k值的变化,分别基于子流程结构紧密性特征和流程结构树,在循环过程中设计增量式方法,对簇中心进行简便的递增;设计合理的有效性指标,对抽象结果模型进行评估,进而生成最佳子流程数;利用真实的流程模型库对设计的方法进行实验验证,得到的最优子流程数与人工设计的结果非常接近。

According to the characteristics of the business process model,this paper proposed a method to determine the optimal number of subprocesses based on the k-means activity clustering algorithm with two different constraints given in the previous work.Combining the assumption for the process structure with the threshold restriction of activity semantics,the method of determining the appropriate upper bound of the number of subprocesses is given in order to reduce the number of iterations.According to the change of kvalue,based on the characteristics of structural compactness of the subprocesses and the refined process structure tree,an incremental approach is designed to simplify the incremental of the cluster centers.A reasonable index is designed to evaluate the abstract result model,and then the optimal number of subprocesses is generated.The proposed method is applied to a process model repository in use,and the number of the optimal subprocesses is very close to the result given by the modelers involved.