南京大学学报（自然科学版）2019，Vol.55Issue(1)：143-153,11.DOI:10.13232/j.cnkij.nju.2019.01.015
自动确定聚类中心的移动时间势能聚类算法
Travel-time based potential clustering by automatic determination of cluster centers
摘要
Abstract
TTHC(Travel-Time based Hierarchical Clustering)is a new potential clustering algorithm.Although it has a good clustering effect,the algorithm needs to set the number of clusters manually,and only allocates samples based on similarity,ignoring the influence of distance and potential values.In response to the above problems,a new algorithm that can automatically determine the clustering centers is proposed.Firstly,the new algorithm calculates the potential values and similarity of each data point,and then determines the parent node of the data point according to similarity,so we can obtain the distance from the parent node.Secondly,according to the similarity and distance between data points and parent nodes and the potential values of data points,the comprehensive consideration value is obtained.The clustering center is automatically determined according to the comprehensive consideration value. Finally,the remaining data points are assigned to clusters whose potential values are smaller and similarity is the largest,and a clustering result is obtained.Comparing the new algorithm with the TTHC algorithm,the experimental results on synthetic datasets and real datasets show that the new algorithm can not only automatically determine the number of clusters,but also adopt a better distribution mechanism and thus has better clustering results.In addition,the new algorithm shows better performance than two other potential clustering algorithms. Key words:clustering,TTHC,travel-time,automatically clustering关键词
聚 类/TTHC/移动时间/自动确定聚类数目Key words
clustering/TTHC/travel-time/automatically clustering分类
信息技术与安全科学引用本文复制引用
陆慎涛,葛洪伟,周竞..自动确定聚类中心的移动时间势能聚类算法[J].南京大学学报（自然科学版）,2019,55(1):143-153,11.基金项目
国家自然科学基金(61305017),江苏省普通高校研究生科研创新计划(KYLX15_1169) （61305017）
