Title: On Density Based Outlier Detection for Uncertain Data
Abstract: Uncertain data generally exist in a large number of applications,such as mobile computing,sensor networks and RFID technology.Outliers detection algorithm can improve the quality of these services.An uncertain data outlier detection algorithm based on density RLOF was proposed.This algorithm introduces a R2-tree structure,which effectively reduces the time complexity when calculating local outlier factor.It also reduces the cost of data updating in the uncertain data set and the maintenance cost of a massive data.The theoretical analysis and experimental results fully prove that the algorithm is effective and feasible.
Publication Year: 2015
Publication Date: 2015-01-01
Language: en
Type: article
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Cited By Count: 1
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