计算机工程与应用2019，Vol.55Issue(17)：89-94,6.DOI:10.3778/j.issn.1002-8331.1806-0278
基于网格查询的局部离群点检测算法
Local Outlier Detection Algorithm Based on Grid Query
摘要
Abstract
In view of the density based Local Outlier Factor(LOF)algorithm, it is necessary to calculate the distance matrix for the k nearest neighbor search, but the time complexity of this algorithm is high, and it is not suitable for the large-scale data set detection. The local outlier detection algorithm based on the grid query(LOGD)is proposed. This algorithm uses the characteristic that the nearest k data points from the data points in the target grid, which must be mem-orable in the target grid or the nearest adjacent grid of the target grid, to improve the neighborhood query operation of the LOF algorithm, and reduce the distance calculation from the neighborhood query. Experimental results show that the algo-rithm has the same detection accuracy as the original LOF algorithm, and effectively reduces the time of outlier detection.关键词
局部离群因子/k近邻/距离矩阵/网格/记忆性/邻域查询Key words
local outlier factor/k-nearest neighbors/distance matrix/grid/memory/neighborhood query分类
信息技术与安全科学引用本文复制引用
牛少章,欧毓毅,凌捷,顾国生..基于网格查询的局部离群点检测算法[J].计算机工程与应用,2019,55(17):89-94,6.基金项目
广东省科技计划基金(No.2014B090901053,No.2014B090908010,No.2015B090906015,No.2015B090906016, No.2017A050501035) （No.2014B090901053,No.2014B090908010,No.2015B090906015,No.2015B090906016, No.2017A050501035）
广州市科技计划项目(No.201807010058). （No.201807010058）
