空间关联规则挖掘在中国农业普查中的应用研究  

A spatial association rules mining application in the second chinese agriculture general investigation

作　　者：张彦丽[1] 

机构地区：[1]西北师范大学地理与环境科学学院,兰州730070

出　　处：《测绘科学》2009年第2期233-236,240,共5页Science of Surveying and Mapping

基　　金：2007年度学校青年教师科研基金项目(NWNU-QN-07-49)

摘　　要：空间关联规则挖掘是一个过程,主要包括数据选取、数据预处理、数据变换、数据挖掘算法实施以及模式解释与评估等。目前,相关研究的重点在于各种空间关联规则挖掘算法的实施,而对其他几个步骤的研究比较少,如多个字段的综合处理、连续数据的离散化等。同时,农业普查数据尤其是第二次全国农业普查数据涵盖了丰富的"三农"信息,像座宝藏,期待人们运用各种技术开发利用。空间关联规则挖掘无疑是挖掘农业普查数据宝藏的最理想工具。本文将空间关联规则挖掘首次引入中国农业普查当中,以其在甘肃农业普查中的应用实例详细描述空间关联规则挖掘各步骤处理过程及各技术关键的处理方法,最后得出一些甘肃省各界最为感兴趣的知识,为甘肃省解决"三农"问题提供决策依据。Spatial association rule mining is a process, including data selection, data preprocessing, data transformation, data mining algorithm implementation and interpretation model and assessment. Currently, the focus of the study related is to all kinds of algorithms implemented of the spatial association rule mining, but the other steps research is relatively small, such as integrated disposal to several fields, discrete and etc. At the same time, the agricultural census data especially the second national agricultural census data cover abundant ＂three-dimensional rural issues＂ information, which is like precious deposits, and expect people to use all kinds of technology to develop and utilize. Spatial association rule mining is undoubtedly the most ideal tool to mine agricultural census data treasures. This paper introduces firstly the spatial mining association rules to China＇s agricultural census, and describes in detail the process and the steps to address the key technical approach. Finally, it draws some Gansup rovince community most interested knowledge, and provides decision-making basis for Gansup rovince solve ＂three-dimensional rural issues＂ .

关 键 词：数据挖掘 空间数据挖掘 关联规则 空间关联规则 

分 类 号：P208[天文地球—地图制图学与地理信息工程]