| 应用改进的共词聚类法探索医学信息学热点主题演变 |
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| 引用本文： | 杨颖,崔雷.应用改进的共词聚类法探索医学信息学热点主题演变[J].现代图书情报技术,2011,27(1):83-87. |
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| 作者姓名： | 杨颖 崔雷 |
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| 作者单位： | 1. 中国医科大学图书馆 沈阳110001;
2. 中国医科大学信息管理与信息系统(医学)系 沈阳 110001 |
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| 摘 要： | 对传统的共词聚类方法进行完善:依据高频低频词界分公式选取高频词;计算粘合力确定每个类别的中心词;对比分析两个时间段,发现主题演变。以医学信息学为例,从PubMed数据库分别下载1999年-2003年和2004年-2008年该学科相关文献,提取主要主题词,进行共词聚类分析,探索医学信息学学科结构的演变过程。
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| 关 键 词： | 共词分析 可视化 聚类 粘合力 齐普夫定律 |
| 收稿时间： | 2010-09-26 |
| 修稿时间： | 2010-11-20 |
Evolution of Topics About Medical Informatics by Improved Co-word Cluster Analysis |
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| Yang Ying Cui Lei,China Medical University,China.Evolution of Topics About Medical Informatics by Improved Co-word Cluster Analysis[J].New Technology of Library and Information Service,2011,27(1):83-87. |
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| Authors: | Yang Ying Cui Lei China Medical University China |
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| Institution: | 1. Library of China Medical University, Shenyang 110001,China;
2. Department of Information Management and Information System (Medicine), China Medical University, Shenyang 110001,China |
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| Abstract: | Co-word cluster method is improved by following ways: high-frequency words are selected according to the formula derived from Zipf’s law; adhesive force is used to identify the core major MeSH words for tagging the content of each cluster; contrastive analysis of two periods helps to find the topics change. The bibliographic data of medical informatics are collected from PubMed in two periods (1999-2003 and 2004-2008). Major MeSH words from the articles are extracted separately to make co-word clusters as to explore the evolution of this subject structure based on comparison of two periods. |
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| Keywords: | Co-word analysis Visualization Cluster Adhesive force Zipf&rsquo s law |
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