针对服务识别算法中聚合度、耦合度等重要指标的优化问题，基于业务流程间的关联度模型，运用网络拓扑聚类算法，引入聚类邻接参数，以聚合度-耦合度为优化目标函数，提出基于赋权网络优化聚类的服务识别算法。结合具体案例，应用Matlab软件进行仿真分析，根据聚合度-耦合度优化模型，选择不同邻接参数取值下的最优聚类效果，验证了该算法在服务识别上的有效性。

Considering the optimization of such indexes as convergence and coupling degree in service identification algorithm, we proposed a service identification algorithm based on Weighed Network Optimized Clustering (WNOC) by using the relational degree model and the method of network topology clustering, introducing the adjacency parameter of clustering, and taking the coupling-convergence degree as the optimized objective function. Simulation was made with Matlab to a certain example, and the optimal clustering result was selected according to the coupling-convergence degree optimized model. The result proves the validity of the method in service identification.