摘要
概括了空间关联规则挖掘的发展现状,引入空间共生域的概念,给出了相关论证,设计了详细的算法步骤。利用该方法可以分割地理连续体、实现数据的离散化处理,由此构造的空间数据库可以应用传统的Apriori算法。同时,针对共生域的异质性问题,给出了障碍距离的模糊隶属度公式。最后,结合应用实际进行挖掘,结果表明该方法适合于发现具有因果关系的空间实体之间的关联性知识。
This paper firstly outlined the developing status of spatial association rule mining, then proposed a new concept called spatial symbiosis neighborhood, and proved the relative definitions. We designed the detailed algorithm and procedure. This method could be used to partition geographical continua and realize discrete processing of geographical data, and the constructed database could be mined by using the classical Apriori-algorithm. Also, in view of the heterogeneity of spatial distribution, we brought forth the fuzzy membership along obstacle path. Finally, by applying our method to practices, the result proved that this method was fit for finding the association knowledge among spatial objects with casual-effect relationship.
出处
《测绘科学技术学报》
北大核心
2007年第1期10-13,17,共5页
Journal of Geomatics Science and Technology
基金
国家973项目(2006CB701305)资助
国家863项目(2006AA12Z146)资助
关键词
空间关联规则
共生域
模糊隶属度
spatial association rule
symbiosis neighborhood
fuzzy membership
