| 汉语文本聚类及其算法设计 |
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| 引用本文： | 陈炯,范卓华,张虎. 汉语文本聚类及其算法设计[J]. 山西电子技术, 2005, 0(2): 29-31 |
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| 作者姓名： | 陈炯 范卓华 张虎 |
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| 作者单位： | [1]山西综合职业技术学院电子分院,山西太原030006／／山西大学计算机与信息技术学院,山西太原030006 [2]山西大学计算机与信息技术学院,山西太原030006 |
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| 摘 要： | 主要针对传统的聚类算法倾向于识别大小类似的球形聚类簇，且对离群数据较为敏感等问题，利用聚类簇代表点选取的方法，同时结合基于人进行聚类判断所遵循的基本原则，即聚类中对象间距离应小于聚类间距离，设计了一种有效的聚类算法，实验结果表明算法是有效的。
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| 关 键 词： | 代表点 聚类簇 聚类中心 汉语文本聚类 算法设计 聚类分析法 |
| 修稿时间： | 2004-12-22 |
Chinese Text Clustering and Algorithm Designing |
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| Chen Jiong, Fan Zhuohua Zhang Hu. Chinese Text Clustering and Algorithm Designing[J]. Shanxi Electronic Technology, 2005, 0(2): 29-31 |
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| Authors: | Chen Jiong Fan Zhuohua Zhang Hu |
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| Affiliation: | Chen Jiong~1,2 Fan Zhuohua2 Zhang Hu2 |
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| Abstract: | Based on the method of selecting the representa ti ve points of clustering clusters and the principle that the distance between obj ects in clusters must be shorter than that between clusters when judging cluster s, this paper focuses on problem that the algorithm of traditional clustering is sensitive to the independent data and inclined to recognize the spheral cluster ing clusters which are similar in size, and designs an effective clustering algo rithm. The result indicates that this algorithm is effective when handling compl icated data. |
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| Keywords: | clustering representative point clustering cluster clustering center |
| 本文献已被 CNKI 维普 等数据库收录！ |
