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基于概念格中紧致依赖的空间数据挖掘方法研究 被引量：1

SPATIAL DATA MINING METHOD BASED ON COMPACT DEPENDENCIES IN CONCEPT LATTICE
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摘要 解决空间数据挖掘的关联规则提取问题。通过应用GIS(Geographic Information System)即地理信息系统,获得空间数据信息,并将空间数据构造概念格,使空间数据和概念格的形成、分析过程统一起来。以"紧致依赖"方法作为主要数据挖掘手段,并在此基础上提出一种基于Apriori剪枝的"紧致依赖"约减方法,从而方便快捷找出满足支持度阈值并且置信度为1的所有关联规则。 The article focuses on solving the problems of spatial data mining and association rules extraction.By applying GIS （geographic information system）,we obtain the information of spatial data and use the data to construct concept lattice,which makes the formation and analysis process in regard to spatial data and concept lattice to be unified.We use the compact dependence as the main means of data mining, and on this basis propose an Apriori pruning-based compact dependent reduction algorithm,therefore conveniently and efficiently find out all the association rules meeting the support threshold and with confidence degree of 1 as well.
作者 曾子维 王鑫 马垣
机构地区 辽宁科技大学软件学院
出处 《计算机应用与软件》 CSCD 北大核心 2014年第2期33-36,139,共5页 Computer Applications and Software
关键词 紧致依赖 概念格 GIS GIS Compact dependency Concept lattice
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
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参考文献11

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共引文献32

同被引文献16

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计算机应用与软件
2014年 第2期

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