Detecting outliers in spatial database

Detecting outlier in spatial database is important for many KDD applications. Existing works in outlier detection don't 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 can't do it by other methods. The experimental results show that our approach is effective and efficient.