| 基于决策支持向量机的中文网页分类器 |
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| 引用本文： | 贺海军,王建芬,周青,曹元大.基于决策支持向量机的中文网页分类器[J].计算机工程,2003,29(2):47-48. |
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| 作者姓名： | 贺海军 王建芬 周青 曹元大 |
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| 作者单位： | 北京理工大学计算机科学工程系,北京,100081 |
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| 摘 要： | 提出了基于决策支持向量机的中文网页分类算法。把支持向量机方法和二叉决策树的基本思想结合起来构成多类别的分类器，用于中文网页分类，从而减少支持向量机分类器训练样本的数量，提高训练效率。实验表明，该方法训练数据规模大大减少，训练效率较高，同时具有较好的精确率和召回率。
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| 关 键 词： | 支持向量机 决策树 网页 分类 |
| 文章编号： | 1000-3428(2003)02-0047-02 |
| 修稿时间： | 2002年2月4日 |
A Chinese Web Page Classifier Based on SVM-decision Tree |
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| HE Haijun,WANG Jianfen,ZHOU Qing,CAO Yuanda.A Chinese Web Page Classifier Based on SVM-decision Tree[J].Computer Engineering,2003,29(2):47-48. |
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| Authors: | HE Haijun WANG Jianfen ZHOU Qing CAO Yuanda |
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| Abstract: | This paper presents a Chinese Web page classification algorithm that is based on SVM-decision tree. The multiple-class classifier is composed of SVM and binary decision tree and used for Chinese Web page classification. It can reduce the train scale of SVM classifier and improve the training efficiency. The experiment shows that it not only reduces the size of train set, but also has very high training efficiency. Its precision and recall are also very good. |
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| Keywords: | Support vector machine(SVM) Decision tree Web page Classification |
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