文章基本信息

标题：The Spatial Outlier Mining Algorithm based on the KNN Graph
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作者：Cao, Lijun ; Liu, Xiyin ; Wang, Zhiping 等
期刊名称：Journal of Software
印刷版ISSN：1796-217X
出版年度：2013
卷号：8
期号：12
页码：3158-3165
DOI：10.4304/jsw.8.12.3158-3165
语种：English
出版社：Academy Publisher
摘要：In order to solve the defect in the spatial outlier mining algorithm that the spatial objects may be affected by their surrounding abnormal neighbors, a Based K-Nearest Neighbor (BKNN) algorithm was proposed based on the working principle of KNN Graph, which could effectively identify the spatial outliers by using cutting edge strategies. The core idea of BKNN is to calculate the dissimilarity of the non-space attribute values the between adjacent objects, and to find the find the largest local outlier or outlier regions by cropping off the edges with the largest dissimilarity. The experiments for the spatial outlier mining algorithm BKNN based on the KNN Graph were carried out in the real datasets FMR and WNV. The example of the algorithm and the time complexity were analyzed and the results were compared to those of the existing classical algorithms, which verified that this algorithm could improve the accuracy of spatial outlier mining and simultaneously mine spatial region outliers.
关键词：Spatial outlier;Spatial region outliers;KNN Graph;BKNN algorithm