计算机工程与应用2016，Vol.52Issue(19)：7-11,5.DOI:10.3778/j.issn.1002-8331.1603-0323
基于密度的异常数据检测算法GSWCLOF
GSWCLOF:density-based outlier detection algorithm on data stream
摘要
Abstract
To improve the inaccuracy and execution efficiency of outlier detection on data stream, a novel density-based outlier detection algorithm named GSWCLOF is proposed. By introducing the concepts of sliding time window and grid, the algorithm cuts a data stream into subsections of data;then after a pruning and filtering process by information entropy, the outliers in left data can be easily identified by local outlier factors. The experimental results finally show the advantages of this new algorithm in accuracy rating and execution efficiency.关键词
数据流检测/滑动窗口/网格/信息熵/离群因子Key words
data stream outlier detection/sliding window/grid/information entropy/local outlier factor分类
信息技术与安全科学引用本文复制引用
李少波,孟伟,璩晶磊..基于密度的异常数据检测算法GSWCLOF[J].计算机工程与应用,2016,52(19):7-11,5.基金项目
国家科技支撑计划（No.2012BAF12B14）；贵州省重大科技专项基金（No.[2014]2001）。 （）
