Detecting graph-based spatial outliers1
Shashi Shekhar, Chang‐Tien Lu, Pusheng Zhang · Intelligent Data Analysis · 2002
Identification of outliers can lead to the discovery of unexpected and interesting knowledge. Existing methods are designed for detecting spatial outliers in multidimensional geometric data sets, where a distance metric is available. In this paper, we focus on detecting spatial outliers in graph st ructured data sets. We define statistical tests, analyze the statistical foundation underlying our approach, design a fast algorithm to detect spatial outliers, and provide cost models for outlier detection procedures. In addition, we provide experimental results from the application of our algorithm on a Minneapolis-St. Paul (Twin Cities) traffic data set to show its effectiveness and usefulness.