| K-Means聚类的多种距离计算方法的文本实验比较 |
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| 引用本文： | 林滨.K-Means聚类的多种距离计算方法的文本实验比较[J].福建工程学院学报,2016,0(1):80-85. |
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| 作者姓名： | 林滨 |
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| 作者单位： | 福州软件职业技术学院计算机系 |
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| 摘 要： | 针对文本类型数据的分类进行研究，用VSM模型和TF IDF技术对文本文件进行了数据样本抽取加权，得到文本相似度矩阵；采用不同样本距离计算方法和K-Means算法对数据进行了聚类实验，获得聚类结果并进行了分析和总结；基于实验结论，研究了不同距离计算方法之间的区别以及适用的数据类型。
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| 关 键 词： | 文本聚类 TF-IDF K-Means 距离计算 |
Experimental comparison of K-Means text clustering by varied distance calculation methods |
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| Lin Bin.Experimental comparison of K-Means text clustering by varied distance calculation methods[J].Journal of Fujian University of Technology,2016,0(1):80-85. |
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| Authors: | Lin Bin |
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| Institution: | Fuzhou Software Technology Vocational College |
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| Abstract: | Text data samples were extracted and weighted and the text similarity matrices were obtained by vector space model (VSM) model and TF-IDF weighting technology. The data clustering was conducted via different distance calculation methods and K-Means algorithm.The clustering results were analysed. The differences among the distance calculation methods and the applicable data types were studied. |
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| Keywords: | text clustering TF-IDF K Means distance calculation |
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