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Evolution of Topics About Medical Informatics by Improved Co-word Cluster Analysis |
Yang Ying1, Cui Lei2 |
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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Received: 26 September 2010
Published: 12 February 2011
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