| 基于kNN的快速WEB文档分类 |
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| 引用本文： | 李杨,曾海泉,刘庆华,胡运发. 基于kNN的快速WEB文档分类[J]. 小型微型计算机系统, 2004, 25(4): 725-729 |
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| 作者姓名： | 李杨 曾海泉 刘庆华 胡运发 |
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| 作者单位： | 1. 复旦大学,计算机系数据库中心,上海,200433
2. 江西省,南昌高等专科学校,计算机系,江西,南昌,330009 |
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| 基金项目： | 国家自然科学基金 ( 60 173 0 2 7)资助 |
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| 摘 要： | 根据测试文档在各个样本类中的分布情况，发现了基于kNN分类的两个有助于减少大量计算的重要性质，在此基础上提出了两个重要算法：排类算法和归类算法，从而构建了一个基于kNN的快速Web文档分类方法．理论与实验表明，这种方法可以在不影响原有准确率的条件下，可提高文档的分类速度．
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| 关 键 词： | 文档分类 kNN 快速分类 排类算法 |
| 文章编号： | 1000-1220(2004)04-0725-05 |
A Fast Document Classification Based on the k-Nearest Neighbor |
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| LI Yang,ZENG Hai quan ,LIU Qing hua ,HU Yun fa. A Fast Document Classification Based on the k-Nearest Neighbor[J]. Mini-micro Systems, 2004, 25(4): 725-729 |
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| Authors: | LI Yang ZENG Hai quan LIU Qing hua HU Yun fa |
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| Affiliation: | LI Yang,ZENG Hai quan 1,LIU Qing hua 1,HU Yun fa 1 |
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| Abstract: | According to the test document distributing in the sample classes, We discover two important properties of the kNN, which can decease greatly the amount of computation during the classifying and give two algorithm EXCLUDING CLASS and INCLUDING CLASS on the based of the two properties. In addition, a fast web document classification paradigm has been presented. Our experimental results illustrate this paradigm can increase the classification speed dramatically while not decreasing its precision of original kNN classification. |
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| Keywords: | document classification k Nearest neighbor excluding class including class |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
