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.