基于FP-Tree的概念格量化约简及其在GIS的应用

Quantitative reduction of concept lattices based on FP-Tree and its application in GIS

GIS的空间数据具有海量性、复杂性的特点,为了能更有效的挖掘隐藏在GIS中的知识引入了概念格技术。然而,又为了解决关联规则生成算法效率低、构造Hasse图效率低及冗余多的问题,提出在FP-Tree的基础上直接生成经过量化约简的频繁概念格。将该算法应用于GIS的空间数据挖掘取得了实际可行的应用结果。

The space data has characteristics of huge volumes and complexity in GIS.In order to mine the hidden knowledge more effectively,the concept lattice technology was introduced in GIS.However,to solve the low efficiency of association rule generation algorithm,low efficiency of structure Hasse diagram,more redundant and other problems were addressed.This paper proposed directly generated frequent concept lattice after quantitative reduction on the basis of FP-Tree.The algorithm achieved practical application of the results which could be applied on spatial data mining in GIS.