基于模糊聚类的多元异构网络数据快速检索方法  

A Fast Retrieval Method of Heterogeneous Network Data Based on Fuzzy Clustering

作　　者：石碧瑶 SHI Biyao(Xi’an Traffic Enginering Institute,Shaanxi Xi’an 710300,China)

机构地区：[1]西安交通工程学院,陕西西安710300

出　　处：《信息与电脑》2022年第13期68-70,共3页Information & Computer

摘　　要：多元异构网络数据具有复杂性高、异构性强以及多样性的特点,使得其在海量多元异构网络数据中很难实现目标数据的快速检索,因此提出了一种基于模糊聚类的多元异构网络数据快速检索方法。通过设计模糊聚类函数模型确定聚类中心,求解模糊聚类的最优解,避免算法陷入局部最优,实现多元异构网络数据的聚类检索,以期为多元异构网络数据检索提供参考与借鉴。Heterogeneous network data is characterized by high complexity,strong heterogeneity and diversity,which makes it difficult to achieve fast retrieval of target data in massive heterogeneous network data.Therefore,a fast data retrieval method based on fuzzy clustering is proposed.The fuzzy clustering function model is designed to determine the clustering center and solve the optimal solution of fuzzy clustering,so as to avoid the algorithm falling into the local optimal and realize the clustering retrieval of multivariate heterogeneous network data,in order to provide certain reference for multivariate heterogeneous network data retrieval.

关 键 词：模糊聚类 多元异构数据 聚类检索 快速检索 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]