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| 基于模糊粒度计算的K-means文本聚类算法研究 | |
| 引用本文： | 张霞,王素贞,尹怡欣,赵海龙.基于模糊粒度计算的K-means文本聚类算法研究[J].计算机科学,2010,37(2):209-211. |
| 作者姓名： | 张霞 王素贞 尹怡欣 赵海龙 |
| 作者单位： | 1. 河北经贸大学计算机中心,石家庄,050061;北京科技大学信息工程学院,北京,100083 2. 河北经贸大学计算机中心,石家庄,050061 3. 北京科技大学信息工程学院,北京,100083 |
| 基金项目： | 国家自然科学基金项目(60374032);;河北省教育厅科研计划项目(2009116)资助 |
| 摘 要： | 传统的K-means算法对初始聚类中心非常敏感,聚类结果随不同的初始输入而波动,算法的稳定性下降。针对这个问题,提出了一种优化初始聚类中心的新算法:在数据对象的模糊粒度空间上给定一个归一化的距离函数,用此函数对所有距离小于粒度d_λ的数据对象进行初始聚类,对初始聚类簇计算其中心,得到一组优化的聚类初始值。实验对比证明,新算法有效地消除了传统K-means算法对初始输入的敏感性,提高了算法的稳定性和准确率。 |
| 关 键 词： | 模糊 粒度 K-means 文本聚类 归一化距离函数 |
| 收稿时间： | 3/9/2009 12:00:00 AM |
| 修稿时间： | 2009/7/20 0:00:00 |
Research of Text Clustering Based on Fuzzy Granular Computing |
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| ZHANG Xi,WANG Su-zhen,YIN Yi-xin,ZHAO Hai-long.Research of Text Clustering Based on Fuzzy Granular Computing[J].Computer Science,2010,37(2):209-211. | |
| Authors: | ZHANG Xi WANG Su-zhen YIN Yi-xin ZHAO Hai-long |
| Affiliation: | 1/a>;2;Computer Center/a>;Hebei University of Economics and Business/a>;Shijiazhuang 050061/a>;China;School of Information Engineering/a>;University of Science and Technology Beijing/a>;Beijing 100083/a>;China |
| Abstract: | The traditional K-means is very sensitive to initial clustering centers and the clustering result will wave with the different initial inpul To remove this sensitivity,a new method was proposed to get initial clustering centers.This method is as follows:provide a normalized distance function in the fuzzy granularity space of data objects,then use the function to do a initial clustering work to these data objects who has a less distance than granularity dλ,then get the initial clustering centers.The test shows this method has such advantages on increasing the rate of accuracy and reducing the program times. |
| Keywords: | Fuzzy Granular computing K-means Text cluster Normalized distance function |
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