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一种网络空间现象同位模式挖掘的新方法
引用本文:田晶,王一恒,颜芬,熊富全.一种网络空间现象同位模式挖掘的新方法[J].武汉大学学报(信息科学版),2015,40(5):652-660.
作者姓名:田晶  王一恒  颜芬  熊富全
作者单位:1武汉大学资源与环境科学学院,湖北武汉,4300792武汉大学地理信息系统教育部重点实验室,湖北武汉,430079
基金项目:国家基础科学人才培养基金资助项目(J1103409);武汉大学大学生创新创业训练资助项目(S2014438)
摘    要:同位模式的挖掘是空间数据挖掘领域关注的热点问题。目前,对于网络空间现象同位模式挖掘的研究较少。本文将欧氏空间已有方法扩展至网络空间,该方法由两个核心步骤组成:①通过对网络进行划分定义同位腜停范ㄍ止叵担虎诙酝止叵到型臣仆贫先范ㄆ涫欠裎荒J健6陨钲谑兄圃煲倒镜耐荒J酵诰蚪辛朔椒ㄋ得鳎谰菁劬醚е械贾虏导鄣娜只贫哉庑┩荒J浇辛硕ㄐ苑治觯ü胍延蟹椒ǖ谋冉弦约巴纾撕募煅檠橹ち吮疚姆椒ǖ挠行浴€

关 键 词:网络空间现象  同位模式  制造业公司  集聚  网络交叉K函数
收稿时间:2013-08-29
修稿时间:2015-05-05

A New Method for Mining Co-location Patterns Between Network Spatial Phenomena
TIAN Jing,WANG Yiheng,YAN Fen,XIONG Fuquan.A New Method for Mining Co-location Patterns Between Network Spatial Phenomena[J].Geomatics and Information Science of Wuhan University,2015,40(5):652-660.
Authors:TIAN Jing  WANG Yiheng  YAN Fen  XIONG Fuquan
Institution:1School of Resources and Environment Science,Wuhan University,Wuhan 430079,China;2Key Laboratory of Geographic Information System,Ministry of Education,Wuhan University,Wuhan 430079,China
Abstract:The mining of co-location patterns is a hot issue in the field of spatial data mining.Howev-er,a little attention has been paid to the co-location patterns between network spatial phenomena.This paper extends an existing approach to mining the co-location patterns between network spatialphenomena.The approach consists of two core stages:①defining a co-location model to have co-oc-currence relations by partitioning the network;②computing the statistical diagnostics for these co-oc-currence relations.The approach has been applied to a case study,which dealt with the mining of theco-location patterns of manufacturing firms in Shenzhen City,China.The co-location patterns havebeen analyzed qualitatively according to the three mechanisms derived from agglomeration economics.The validation of the approach has been verified by the comparison with the existing method and thenetwork cross K-function.
Keywords:network spatial phenomena  co-location patterns  manufacturing firms  agglomeration  network cross K-function
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