| 基于双聚类方法的生物医学信息学文本数据挖掘研究 |
| |
| 引用本文： | 于跃,徐志健,王珅,王伟.基于双聚类方法的生物医学信息学文本数据挖掘研究[J].图书情报工作,2012,56(18):133-136. |
| |
| 作者姓名： | 于跃 徐志健 王珅 王伟 |
| |
| 作者单位： | 1. 吉林大学公共卫生学院医药信息与卫生管理学系 长春 130021;2. 吉林大学中日联谊医院 长春 130021 |
| |
| 摘 要： | 运用TDA和gCluto软件对SCI数据库中近5年的相关文献进行处理,获得双聚类矩阵图,经分析后得到该学科领域近年来的期刊研究主题方向与热点。结论认为,双聚类方法能够很好地反映学科发展状况及研究热点,从而为医学人员提供有价值的信息与知识,值得进一步研究与推广。
|
| 关 键 词： | 生物医学信息学 聚类分析 双聚类 数据挖掘 |
| 收稿时间： | 2012-05-28 |
Text Data Mining in Biomedical Informatics Based on Biclustering Method |
| |
| Yu Yue,Xu Zhijian,Wang Shen,Wang Wei.Text Data Mining in Biomedical Informatics Based on Biclustering Method[J].Library and Information Service,2012,56(18):133-136. |
| |
| Authors: | Yu Yue Xu Zhijian Wang Shen Wang Wei |
| |
| Institution: | 1. Department of Medical Informatics & Health Management, School of Public Health, Jilin University, Changchun 130021;2. China-Japan Union Hospital, Jilin University, Changchun 130021 |
| |
| Abstract: | In this paper, the authors retrieve SCI database to get the relating literatures during the recent 5 years and extract the recording information by TDA software and gCluto software. The outcomes indicate the research subject areas and hot spots in the biclustering figure. The conclusion is that biclustering techniques can reflect the development in a given field,and provide valuable medical information and knowledge for medical researchers. Further research and extension is needed to confirm the worth of these technologies. |
| |
| Keywords: | biomedical informatics cluster analysis biclustering data mining |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《图书情报工作》浏览原始摘要信息 |
| 点击此处可从《图书情报工作》下载免费的PDF全文 |
|
