计算机工程与应用2019，Vol.55Issue(20)：43-51,9.DOI:10.3778/j.issn.1002-8331.1903-0246
基于共享k-近邻与共享逆近邻的密度峰聚类
Density Peak Clustering Based on Shared k-Nearest Neighbors and Shared Reverse Nearest Neighbors
摘要
Abstract
In order to better solve the problem of density imbalance and characterize the similarity measure of high-dimensional data, a density peak clustering algorithm based on shared k -nearest neighbors and shared reverse nearest neighbors is proposed. This algorithm first calculates the shared k-nearest neighbor number and the shared reverse near-est neighbor number of two points, and combines them with the Euclidean distance to determine the shared similarity between the two points. In the following it defines shared density of a point by sum of shared similarities between this point and its reverse nearest neighbors, and then selects the cluster center by the shared density. The experimental results show that the clustering results of the algorithm on the artificial dataset and the real dataset are more accurate than other density clustering algorithms. So the algorithm can better deal with the density imbalance problem, and also improves the clustering accuracy of high-dimensional data.关键词
密度峰聚类/共享k-近邻与共享逆近邻/共享相似度/共享密度Key words
density peak clustering/shared k-nearest neighbors and shared reverse nearest neighbors/shared similarity/shared density分类
信息技术与安全科学引用本文复制引用
高月,杨小飞,马盈仓,汪义瑞..基于共享k-近邻与共享逆近邻的密度峰聚类[J].计算机工程与应用,2019,55(20):43-51,9.基金项目
国家自然科学基金(No.11501435). （No.11501435）
