摘要
目的:本文将双聚类的方法用于同被引分析,即在同被引分析中充分考虑列属性的特点,在行和列两个方向,对高频同被引文献及其引用文献进行聚类分析,同时实现同被引聚类分析和基于高被引论文的引文耦合分析,可探索某领域的基础结构与研究热点。方法:本文以WebofScience网络数据库中的护理研究文献为例,对高频被引论文进行同被引双向聚类分析。结果与结论:聚类结果通过g Cluto软件进行可视化显示,并结合护理研究知识对聚类结果进行分析解释,总结该领域的学科基础结构和研究热点。
Purpose: In this paper, biclustering was used in co-citation analysis. Co-citations with high frequency and citations were clustered at the same time, so that co-citation analysis and citation coupling analysis were performed simultaneously to explore the intellectual base and research front of certain field. Method: Co-citation biclustering analysis of the highly cited papers was performed using the papers on nursing in Web of Science as data source. Result and conclusion: The visualization results were visualized by g Cluto. The intellectual base of nursing research and its hot research spots were summarized.
作者
杨颖
崔雷
Yang Ying;Cui Lei(Library of China Medical Universit;College of Medical Information, China Medical Universit)
出处
《图书馆杂志》
CSSCI
北大核心
2018年第5期67-73,共7页
Library Journal
基金
辽宁省教育厅科学研究一般项目"大数据时代高校图书馆面向重点学科的综合情报服务研究"(项目编号:W2014106)的研究成果之一
关键词
同被引分析
双聚类
gCluto
Co-citation analysis
Biclustering analysis
gCluto