从GIS数据库中挖掘空间离群点的一种高效算法

基金项目: 国家自然科学基金资助项目(40301038)

详细信息

Fast Mining of Spatial Outliers from GIS Database

¹ Nanjing Institute of Geography and Limnology,CAS,73 East Beijing Road,Nanjing 210008,China;² Department of Computer Science and Engineering,Ha'erbin Institute of Technology,92 Xidazhi Street,Ha'erbin 150001,China

Funds: 国家自然科学基金资助项目(40301038)

摘要: 根据GIS的空间特性,借鉴已有的定义和概念,定义了空间离群点是和在其非空间属性邻域内其他空间对象在空间位置上差异十分显著的空间对象,并设计了SOD算法。实验结果验证了SOD算法的有效性和优越性,给出了从GIS数据库中挖掘空间离群点的一般步骤。
- GIS /
- 数据挖掘 /
- 空间离群点 /
- 最近邻
Abstract: On the basis of the spatial characteristics of GIS, an alternative viewpoint for defining and discovering spatial outliers from GIS is proposed,in which the spatial location of a spatial outlier is significantly far from other spatial objects in its neighborhood determined by non-spatial attribute.Then the SOD algorithm is proposed and analyzed in detail.Experimental results on synthetic datasets demonstrate that the proposed approach can effectively and efficiently identify spatial outliers in large spatial data sets.Finally,the authors give the general procedure to mine the spatial outliers from GIS database.
- IS /
- data mining /
- spatial outlier /
- nearest neighbor