Parallelism of spatial data mining based on autocorrelation decision tree

作     者：Zhang Shuyu Zhu Zhongying 

作者机构：Dept. of Automation Shanghai Jiaotong Univ. Shanghai 200030 P. R. China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2005年第16卷第4期

页      面：947-956页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 

主　　题：spatial databases autocorrelation attribute decision tree parallelism. 

摘      要：Define and theory of autocorrelation decision tree （ADT） is introduced. In spatial data mining, spatial parallel query are very expensive operations. A new parallel algorithm in terms of autocorrelation decision tree is presented. And the new method reduces CPU- and I/O-time and improves the query efficiency of spatial data. For dynamic load balancing, there are better control and optimization. Experimental performance comparison shows that the improved algorithm can obtain a optimal accelerator with the same quantities of processors. There are more completely accesses on nodes. And an individual implement of intelligent information retrieval for spatial data mining is presented.