广东工业大学学报Issue(3)：39-43,5.DOI:10.3969/j.issn.1007-7162.2014.03.007
一种应用于噪声点分布密集环境下的噪声点识别算法
A Recognition Algorithm of Noise Applied to Environments with Intensive Noise-data Distribution
摘要
Abstract
By combining the PageRank algorithm with the features of intensive noise-data to improve the noise-data recognition rate of DBSCAN in environments with intensive Noise-Point distribution , it struc-tured the inner-cluster mapping function for voting , and proposed the inter-cluster voting noise recognition algorithm-NoiseRank .Experimental results show that in environments with intensive Noise-Point distribu-tion, the Noise-data recognition rate of NoiseRank is much higher than that of DBSCAN .关键词
噪声点识别/噪声点分布密集/簇间投票/DBSCAN/PageRankKey words
noise-data recognition/environments with intensive noise-point distribution/inner-cluster voting/DBSCAN/PageRank分类
信息技术与安全科学引用本文复制引用
陈平华,周鹏..一种应用于噪声点分布密集环境下的噪声点识别算法[J].广东工业大学学报,2014,(3):39-43,5.基金项目
广东省教育部产学研结合项目 （）
