Chinese Academy of Surveying and Mapping, China
Jiping Liu has received his MSc degree in Computer Aided Cartography from Wuhan Technical University of Surveying and Mapping, and PhD degree (2004) in Cartography and GIS from the PLA Information Engineering University. He has done his Post-doctoral studies from Tsinghua University. Now he is a Professor in Chinese Academy of Surveying and Mapping. He has published 2 books and more than 100 papers in reputed journals. He has also been serving as a Director of the E-government Information Commission of China Association for Geographic Information Society and a Member of Commission on Theoretical Cartography, International Cartographic Association since 2011. His research interests are in the areas of Spatial Data Mining, Government Geographic Information Service and Image Processing.
In view of the existing spatial outlier mining algorithms which cannot adapt to the needs of large-scale spatial data mining, this paper presents a spatial outlier mining algorithm based on distributed system. Firstly, this paper proposes the use of space filling curve to partition the data set, and speed up the nearest neighbor search of the target point. Secondly, using the theory of information entropy to define the spatial outlier factor, taking into account the impact of different attributes of multidimensional data on the outliers, the algorithm can automatically calculate the weight of each attribute according to the original features of the data. At the same time, the influence of spatial factors on the outlier factor is defined by the inverse distance weight. Experiments show that the efficiency of this algorithm is much higher than that of the traditional algorithm, and the accuracy of outlier mining is more than 90 percent.