| 基于密度优化的KNN算法的研究 |
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| 引用本文： | 陈东晓,陈庆奎.基于密度优化的KNN算法的研究[J].上海理工大学学报,2010,32(5). |
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| 作者姓名： | 陈东晓 陈庆奎 |
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| 作者单位： | 上海理工大学 光电信息与计算机工程学院, 上海200093;上海理工大学 光电信息与计算机工程学院, 上海200093 |
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| 摘 要： | 通过对样本网页文本的影响因子特征提取,构建向量空间模型,同时利用OPTICS算法密度无关性,改进了KNN算法.实验表明,该算法增强了结果的稳定性,并产生质量较高的聚类结果.
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| 关 键 词： | KNN算法 Web特征 奇异值分解 OPTICS算法 |
Density optimization based KNN algorithm |
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| CHEN Dong xiao and CHEN Qing qui.Density optimization based KNN algorithm[J].Journal of University of Shanghai For Science and Technology,2010,32(5). |
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| Authors: | CHEN Dong xiao and CHEN Qing qui |
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| Abstract: | A vector space model by abstracting document features from Web pages of samples by using influencial factors was established.The advantage of density independence of OPTICS algorithm was taken for,improving the KNN algorithm to overcome the shortcoming of inadaptability to clustering of low density point.Experiments show that the algorithm can enhance the stability of the results and produce higher quality clustering results. |
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| Keywords: | KNN algorithm Web features singular value decomposition OPTICS algorithm |
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