基于网格聚类中边界点的处理  

作　　者：江先伟[1] 

机构地区：[1]福建船政交通职业学院,福建福州350007

出　　处：《科技视界》2012年第34期67-67,53,共2页Science & Technology Vision

摘　　要：基于网络聚类中,效率与精度是一对矛盾。聚类的边界代表了一种潜在的模式,对数据挖掘有着重要的意义。文中介绍了边界点处理相关工作的基础上,提出一种应用密度的思想对边界点扩展的处理技术,可在一定程度上提高基于网格聚类的精度。There always is contradiction between efficiency and accuracy on the grid-based clustering. The boundary of clusters is a potential model, which is very important for data mining. Here introduces the basic processing of boundary point related work, and boundary processint technology base on the ideas of application of density. To improve the reliability of grid-based clustering results in a certain extent.

关 键 词：网格聚类 边界点 核心点 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]