| 肿瘤领域关键词共现网络聚类方法研究 |
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| 引用本文： | 宋培彦,李丹丹.肿瘤领域关键词共现网络聚类方法研究[J].医学信息学杂志,2018,39(8):51-57. |
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| 作者姓名： | 宋培彦 李丹丹 |
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| 作者单位： | 中国科学技术信息研究所 北京 100038,首都经济贸易大学信息学院 北京 100070 |
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| 基金项目： | 2016国家社会科学基金项目“基于知识组织的科研项目评审专家发现研究”（项目编号：16BTQ079）；2017年度中国科学技术信息研究所创新研究基金面上项目“面向国家科技大数据的知识图谱动态构建方法研究”（项目编号：MS2017-06）。 |
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| 摘 要： | 在共词计算基础上引入两步聚类算法，设计术语遴选、两步聚类和评价迭代聚类流程。以肿瘤领域术语为例构建共现矩阵和关系网络，采用两步聚类法进行自动聚类和实证研究，对其区分度进行评测。实验结果表明该方法聚类效果较好。
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| 关 键 词： | 知识组织 自动聚类 术语 知识网络 |
| 收稿时间： | 2018/5/14 0:00:00 |
Study on the Clustering Method of Keyword Co-occurrence Network in the Field of Tumor |
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| SONG Pei-yan and LI Dan-dan.Study on the Clustering Method of Keyword Co-occurrence Network in the Field of Tumor[J].Journal of Medical Informatics,2018,39(8):51-57. |
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| Authors: | SONG Pei-yan and LI Dan-dan |
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| Institution: | Institute of Scientific and Technical Information of China, Beijing 100038, China and School of Information, Capital University of Economics and Business, Beijing 100070, China |
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| Abstract: | To introduce the two-step clustering algorithm based on the co-word calculation, the terminology selection, two-step clustering and the clustering processes of evaluation iteration are designed. Taking the terminology in the area of tumor as an example, the co-occurrence matrix and relational network is built. To adopt the two-step clustering method to carry out the automatic clustering and empirical study, the discrimination is evaluated. The results of the tests show that the clustering effect of the method is good. |
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| Keywords: | Knowledge organizaiton Automatic clustering Terminology Knowledge network |
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