首页    期刊浏览 2025年07月17日 星期四
登录注册

文章基本信息

  • 标题:The Study About the Analysis of Responsiveness Pair Clustering Tosocial Network Bipartite Graph
  • 本地全文:下载
  • 作者:Akira Otsuki ; Masayoshi Kawamura
  • 期刊名称:Advanced Computing : an International Journal
  • 印刷版ISSN:2229-726X
  • 电子版ISSN:2229-6727
  • 出版年度:2013
  • 卷号:4
  • 期号:6
  • DOI:10.5121/acij.2013.4601
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:In this study, regional (cities, towns and villages) data and tweet data are obtained from Twitter, and extract information of "purchase information (Where and what bought)" from the tweet data by morphological analysis and rule-based dependency analysis. Then, the "The regional information" and the "Theinformation of purchase history (Where and what bought information)" are captured as bipartite graph, and Responsiveness Pair Clustering analysis (a clustering using correspondence analysis as similarity measure) is conducted. In this study, since it was found to be difficult to analyze a network such as bipartite graph having limitations in links by using modularity Q, responsiveness is used instead of modularity Q as similarity measure. As a result of this analysis, "regional information cluster" which refers to similar "Theinformation of purchase history" nodes group is generated. Finally, similar regions are visualized by mapping the regional information cluster on the map. This visualization system is expected to contribute as an analytical tool for customers' purchasing behaviour and so on
  • 关键词:Big Data analysis; customers' purchasing behaviour analysis; Data Mining; Database
国家哲学社会科学文献中心版权所有