计算机工程与应用2011，Vol.47Issue(2)：121-123,3.DOI:10.3778/j.issn.1002-8331.2011.02.038
扩散模式的聚类算法研究
Research of clustering algorithm based on diffusion model.
摘要
Abstract
Aiming at the various distribute clustering problems in diffusion model for all data points, a new clustering algorithm(CDD) based on the change of density is proposed. CDD searches the core point using a typical clustering algorithm (DBSCAN) based on the density, it calculates the direction, speed and acceleration of density diffused through analyzing the diffusion rule of data sample and its around the point' density,then completes the sample points' clustering. The experimental results show that compared with DBSCAN,CDD can cluster the diffusion model accurately,and has strong anti-noise-interference ability for the non-diffusion model which makes it easier to determine the merits of the parameters.关键词
聚类/数据挖掘/扩散模式Key words
clustering/data mining/diffusion model分类
信息技术与安全科学引用本文复制引用
黄俊恒,孙玉山,朱东杰..扩散模式的聚类算法研究[J].计算机工程与应用,2011,47(2):121-123,3.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60973077/F020504). （the National Natural Science Foundation of China under Grant No.60973077/F020504）
