document: Detecting graph-based spatial outliers : algorithms and applications ( a summary of results ) Identification of outliers can lead to the discovery of unexpected , interesting , and useful 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 structured data sets . We define statistical tests , analyze the statistical foundation underlying our approach , design several fast algorithms to detect spatial outliers , and provide a cost model for outlier detection procedures . In addition , we provide experimental results from the application of our algorithms on a Minneapolis-St . Paul ( Twin Cities ) traffic dataset to show their effectiveness and usefulness .
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