DocumentCode :
3302252
Title :
A Grid-based Spatial Association Mining Method
Author :
Zhao, Xiaohui ; Fang, Yu
Author_Institution :
Inst. of Remote Sensing & Geographic Inf. Syst., Peking Univ., Beijing
fYear :
2007
fDate :
16-18 Aug. 2007
Firstpage :
600
Lastpage :
607
Abstract :
The grid is a distributed computing infrastructure that supports the sharing and coordinated use of various resources in virtual organizations. The grid can be used for compute intensive tasks and data intensive applications. Data mining algorithms are intensive compute and data, and spatial data are heterogeneous, multidimensional and stored at various places. Therefore, the grid can provide a computing and data management platform for spatial data. In this paper, a grid-based spatial association mining method, grid-based spatial apriori algorithm (GSAA), is presented to find hidden relations and regularities in the grid framework. The main thoughts of GSAA are described. We adopt GSAA in a traffic information system. It discovers the inherent connections and relative factors, and finds the causes of traffic accidents and the places where the traffic accidents often take place. It proves to improve the traffic conditions of cities in the grid framework effectively.
Keywords :
data mining; grid computing; data management platform; data mining algorithms; distributed computing infrastructure; grid-based spatial apriori algorithm; grid-based spatial association mining method; traffic accidents; traffic information system; virtual organizations; Association rules; Cities and towns; Data analysis; Data mining; Distributed computing; Geographic Information Systems; Grid computing; Information analysis; Road accidents; Spatial databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Grid and Cooperative Computing, 2007. GCC 2007. Sixth International Conference on
Conference_Location :
Los Alamitos, CA
Print_ISBN :
0-7695-2871-6
Type :
conf
DOI :
10.1109/GCC.2007.12
Filename :
4293835
Link To Document :
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