Title :
VOD: A Novel Outlier Detection Algorithm Based on Voronoi Diagram
Author :
Qin, Wen ; Qu, Jilin
Author_Institution :
Sch. of Comput. & Inf. Eng., Shandong Univ. of Finance, Jinan, China
Abstract :
Outlier mining is an important branch of data mining and has attracted much attention recently. The density-based method LOF is widely used in application. However, the complexity of the method is quadratic to size of the dataset, and it is very sensitive to its parameters MinPts. In this paper, we propose a new outlier detection method based on Voronoi diagram, called Voronoi based Outlier Detection (VOD), to provide highly-accurate outlier detection and reduces the time complexity from O(n2) to O(nlogn).
Keywords :
computational complexity; computational geometry; data mining; MinPts parameters; Voronoi diagram; data mining; density based method; outlier detection algorithm; Approximation algorithms; Clustering algorithms; Complexity theory; Data mining; Estimation; Information systems; Nearest neighbor searches; Voronoi diagram; algorithm; data mining; outlier detection;
Conference_Titel :
Information Engineering (ICIE), 2010 WASE International Conference on
Conference_Location :
Beidaihe, Hebei
Print_ISBN :
978-1-4244-7506-3
Electronic_ISBN :
978-1-4244-7507-0
DOI :
10.1109/ICIE.2010.105
