空间关联规则挖掘技术的研究及应用
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摘要
空间数据挖掘是指从空间数据库中提取用户感兴趣的空间模式与特征、空间与非空间的普遍关系及其它一些隐含在空间数据库中的普遍数据特征。文中首先介绍了空间数据挖掘和空间关联规则挖掘技术。结合空间数据的关联特性,针对传统关联规则挖掘方法的不足,提出了三种适合空间数据挖掘的空间关联规则挖掘算法:基于空间拓扑关系挖掘算法、基于空间距离挖掘算法和基于空间方位关系挖掘算法,并通过实例验证了方法的有效性。最后对未来可能研究的方向做了分析和展望。
Spatial data mining(SDM) refers to picking up interesting rules from spatial database,such as spatial patterns and characteristics,the universal relations of spatial and non-spatial data and other universal implicated in spatial data.Introduce the spatial data mining and the spatial association rules technology first.Based on the shortage of the traditional association rule mining method,propose three algorithms for spatial association rules including spatial topological relation based mining method,spatial distance based mining method and spatial direction based mining method,which was proved to be effective through the experiment.Finally,made the analysis and forecast to the possible direction of future research.
Spatial data mining(SDM) refers to picking up interesting rules from spatial database,such as spatial patterns and characteristics,the universal relations of spatial and non-spatial data and other universal implicated in spatial data.Introduce the spatial data mining and the spatial association rules technology first.Based on the shortage of the traditional association rule mining method,propose three algorithms for spatial association rules including spatial topological relation based mining method,spatial distance based mining method and spatial direction based mining method,which was proved to be effective through the experiment.Finally,made the analysis and forecast to the possible direction of future research.
引文
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[8]Han Jiawei,Kamber M.数据挖掘:概念与技术[M].范明,孟小峰,译.北京:机械工业出版社,2007.
[9]Bembenik R,Rybifiski H.Mining Spatial Association Ruleswith No Distance Parameter[C]//Proc.of Intelligent Infor-mation Processing and Web Mining.Berlin:Springer,2006:499-508.
[10]张宏,温永宁,刘爱利,等.地理信息系统算法基础[M].北京:科学出版社,2006.
[11]李东平,姚远.GIS的发展趋势与数字地震应急救灾的实现技术[J].计算机技术与发展,2011,21(1):214-217.
[12]吕曹芳.基于GIS的空间数据挖掘研究进展[J].皖西学院学报,2010,26(2):43-46.
[2]李德仁,王树良,史文中,等.论空间数据挖掘和知识发现[J].武汉大学学报:信息科学版,2001,26(6):491-499.
[3]王劲峰.地图的定性和定量分析[J].地球信息科学学报,2009,11(2):169-175.
[4]Chen Y L,Chen J M,Tung C W.A data mining approach forretail knowledge discovery with consideration of the effect ofshelf-space adjacency on sales[J].Decision Support Sys-tems,2006,42(3):1503-1520.
[5]黄杏元,劲松,汤勤.地理信息系统概论[M].北京:高等教育出版社,2001.
[6]Ester M,Hans-Peter K,Sander J.Knowledge Discovery inSpatial Database[C]//Proc of Conf.on Artificial Intelli-gence.Bonn,Germany:[s.n.],1999.
[7]Ester M,Frommelt A,Kriegel H,et al.Spatial Data Mining:Database Primitives,Algorithms and Efficient DBMS Support[J].Data Mining and Knowledge Discovery,2000,4(2/3):193-216.
[8]Han Jiawei,Kamber M.数据挖掘:概念与技术[M].范明,孟小峰,译.北京:机械工业出版社,2007.
[9]Bembenik R,Rybifiski H.Mining Spatial Association Ruleswith No Distance Parameter[C]//Proc.of Intelligent Infor-mation Processing and Web Mining.Berlin:Springer,2006:499-508.
[10]张宏,温永宁,刘爱利,等.地理信息系统算法基础[M].北京:科学出版社,2006.
[11]李东平,姚远.GIS的发展趋势与数字地震应急救灾的实现技术[J].计算机技术与发展,2011,21(1):214-217.
[12]吕曹芳.基于GIS的空间数据挖掘研究进展[J].皖西学院学报,2010,26(2):43-46.
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