广西师范大学学报（自然科学版） ›› 2011, Vol. 29 ›› Issue (2): 167-173.

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基于凝聚层次聚类的co-location模式挖掘

高世健, 王丽珍, 冯岭, 陈红梅   

  1. 云南大学信息学院,云南昆明650091
  • 收稿日期:2011-05-07 发布日期:2018-11-19
  • 通讯作者: 王丽珍(1962—),女,云南丽江人,云南大学教授,博士。E-mail:lzhwang2005@126.com
  • 基金资助:
    国家自然科学基金资助项目(61063008);云南省教育厅研究基金资助项目(09Y0048);云南大学科学研究基金资助项目(2009F29Q)

Co-location Patterns Mining Based on Agglomerative Hierarchical Clustering

GAO Shi-jian, WANG Li-zhen, FENG Ling, CHEN Hong-mei   

  1. School of Information Science and Engineering,Yunnan University,Kunming Yunnan 650091,China
  • Received:2011-05-07 Published:2018-11-19

摘要： 空间的co-location模式代表一组空间对象的子集,它们的实例在空间中频繁地关联,它是空间数据挖掘的重要研究方向。本文首先介绍co-location模式挖掘的基本算法,然后提出一种新的挖掘算法,算法先对空间数据进行凝聚层次聚类,在聚类结果上挖掘co-location模式,最后对这种新的算法作实验评估。

关键词: 空间数据挖掘, co-location模式, 凝聚层次聚类, 参与度

Abstract: Spatial co-location patterns represent the subsets of features whose instances are frequently located together in geographic space.It is an important research in the spatial data mining.Firstly,this paper introduces thebasic algorithms of co-location mining.Secondly,a new algorithm is proposed,which clusters the spatial data by the agglomerative hierarchical clustering algorithm,and mines co-location patterns based on the clustering result.Finally,the experimental evaluations of the new algorithm are presented.

Key words: spatial data mining, co-location patterns, agglomerative hierarchical clustering, participation index

中图分类号: 

  • TP392
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