计算机工程 ›› 2011, Vol. 37 ›› Issue (18): 38-40.doi: 10.3969/j.issn.1000-3428.2011.18.013

• 软件技术与数据库 • 上一篇    下一篇

基于空间布局约束的拓扑关联规则挖掘

方 刚   

  1. (重庆三峡学院数学与计算机科学学院,重庆 404000)
  • 收稿日期:2011-04-11 出版日期:2011-09-20 发布日期:2011-09-20
  • 作者简介:方 刚(1978-),男,副教授、硕士,主研方向:数据挖掘,数据库技术,地理信息系统
  • 基金项目:

    重庆市万州区科技攻关计划基金资助项目(2010-23-01);重庆三峡学院科研基金资助项目(11ZD-18)

Topology Association Rule Mining Based on Spatial Layout Constraint

FANG Gang   

  1. (College of Mathematics and Computer Science, Chongqing Three Gorges University, Chongqing 404000, China)
  • Received:2011-04-11 Online:2011-09-20 Published:2011-09-20

摘要: 在空间拓扑关联挖掘中,为提取包含指定空间布局关系的拓扑关联规则,提出一种基于空间布局约束的拓扑关联规则挖掘算法,该算法能够在多空间关系模式下,挖掘包含空间布局约束的拓扑关联规则,将空间关系事务转换成整数,通过空间布局约束重构非目标空间对象类的权值向量,用重构权位值递减构建候选频繁项,并用布尔运算计算其支持数。实验结果表明,与传统挖掘算法相比,该算法的挖掘速度更快、更有效。

关键词: 拓扑关联, 空间布局约束, 向量重构, 重构权位值, 空间数据挖掘

Abstract: In spatial topology association mining, in order to extract topology association rule with given spatial layout relation, this paper proposes an algorithm of topology association rule mining based on spatial layout constraint, which is able to extract topology association rule with spatial layout constraint in multi-spatial relation patterns. The algorithm turns spatial relation transaction into integer, and refactors weight vector of non-target spatial object class via spatial layout constraint, and decreases refactoring weight value to generate candidate frequent item set, and computes its support via Boolean operation. When mining topology association rule with given spatial layout relation, the algorithm is faster and more efficient than traditional mining algorithm by these ways.

Key words: topology association, spatial layout constraint, vector refactoring, refactoring weight, spatial data mining

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