Spatial outlier detection: data, algorithms, visualizations
SSTD'11 Proceedings of the 12th international conference on Advances in spatial and temporal databases
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Detecting outlier in spatial database is important for many KDD applications. Existing works in outlier detection donýt distinguish between spatial dimension and non-spatial dimension or have poor efficiency. In this paper, we proposed a new measure to identify spatial outliers. We defined spatial outlier factor (SOF) to detect spatial outliers efficiently, and proposed a algorithm (SOFind) to identify them. SOF can successfully identify significant outliers and filtrate some meaningless outliers but canýt do it by other methods. The experimental results show that our approach is effective and efficient.