本文已被：浏览 1608次 下载 3377次
Received:November 10, 2010 Revised:December 13, 2010
Received:November 10, 2010 Revised:December 13, 2010
中文摘要: 空间聚类一直是空间数据挖掘研究的热点之一。现有的聚类方法大都局限于根据空间位置来进行空间聚类的，忽略了空间对象的专题属性，从而导致空间聚类结果有时完全不符合人的空间认知，缺乏合理的解释。为此，综合考虑空间对象的位置和专题属性，提出了一种基于概念格的空间聚类(Concept Lattices Based SpatialCluster, CLBSC)方法。该方法通过构建多维专题属性的概念格，简化了空间聚类计算。最后，通过两组实验对CLBSC 算法进行了验证分析，研究结果表明：所提出的CLBSC 算法是一种具有
Abstract:Spatial clustering is a hot issue in the field of spatial data mining. For a spatial object, the spatial location and
the thematic attributes of spatial data are the inherent characteristics. However, the existing approaches mostly regard
only the distance of spatial location as the similarity metric of spatial clustering, ignoring the thematic attributes of
spatial objects. The results of these spatial clustering methods are not reasonable. Thus, a new spatial clustering method,
named Concept Lattices Based Spatial Cluster (CLBSC for short) is proposed in this paper. The method considers both
the spatial distance and attribute distance, and it simplifies the computation via building multi-dimensional attribute
lattices. Furthermore, many concepts about CLBSC are expounded and its algorithm is narrated in detain. Finally, two
experiments demonstrate that CLBSC algorithm is able to find more outlier and improve the reliability of spatial
clustering using the Same Lattices Number.
文章编号： 中图分类号： 文献标志码：
基金项目:国家高技术研究发展计划(863)(2009AA12Z206);湖南省自然科学基金(09JJ6061)
引用文本：
殷俊华,李光强,陈翼,邓敏.基于概念格的空间聚类方法.计算机系统应用,2011,20(6):103-108
YIN Jun-Hua,LI Guang-Qiang,CHEN Yi,DENG Min.A Spatial Clustering Method Based on Concept Lattices.COMPUTER SYSTEMS APPLICATIONS,2011,20(6):103-108
殷俊华,李光强,陈翼,邓敏.基于概念格的空间聚类方法.计算机系统应用,2011,20(6):103-108
YIN Jun-Hua,LI Guang-Qiang,CHEN Yi,DENG Min.A Spatial Clustering Method Based on Concept Lattices.COMPUTER SYSTEMS APPLICATIONS,2011,20(6):103-108
