情报杂志Issue(11)：40-44,39,6.
基于社会网络的学科主题聚类研究
A Clustering Study of Subject Theme Based on Social Network
摘要
Abstract
In this paper, the authors applied the method of social network analysis to the subject theme clustering. The authors built a co-words network based on the 3244 articles collected from CNKI, then clustered the keywords using the Blondel community detecting algo-rithm, and finally used the Z-value to detect the core circle of the community. At the end, the three selected appropriate examples were used to evaluate the two algorithms, the results showed that the “Blondel community detecting algorithm” runs very good although there exists some problems, and the “Z-value” algorithm runs perfectly good in every aspects. According to these methods, the subject theme clustering of Library and Information Science was concluded.关键词
学科主题聚类/社会网络/社区发现/Z-value/核心圈Key words
clustering of subject theme/social network/community detecting/Z-value core/circle分类
社会科学引用本文复制引用
朱梦娴,程齐凯,陆伟..基于社会网络的学科主题聚类研究[J].情报杂志,2012,(11):40-44,39,6.基金项目
教育部人文社会科学基地重大项目“面向细粒度的网络信息检索模型及框架构建研究”(编号:10JJD630014) （编号:10JJD630014）
国家自然科学基金面上项目“基于语言模型的通用实体检索建模及框架实现研究”(编号:71173164)的研究成果之一 （编号:71173164）
