【摘要】 论文将常用于关系型、事务型数据库的面向属性归纳的方法和关联规则挖掘方法扩展至空间数据库 ,开发了适用于地理信息系统 (GIS)的空间数据挖掘工具———GISMiner,并将其应用于从农田GIS中挖掘农田使用情况的空间特征规则 ,以及从农产品市场GIS中挖掘农产品价格与铁路、国道和河流间的空间关联规则实验 .结果表明 ,GISMiner是一个实用的、能适用于GIS且能挖掘多种知识类型的数据挖掘工具更多还原

【Abstract】 Data Mining has become one of the hottest topics in the fields of artificial intelligence and databases, and its scope of application has been extended from relational databases and transaction databases to spatial databases. This research extends an attribute-oriented induction approach and association rule mining method toward spatial databases, and has developed a spatial data mining tool--GISMiner. As experiments, GISMiner is applied in mining characteristic rules of farmland usage from a farm GIS, and spatial association rules among farm product price, railway, national highway and river from farm products market GIS. Results show that GISMiner is a data mining tool which is practical and suitable for GIS and can discover multiple types of knowledge.更多还原