| 一种四维向量空间模型的Web新闻文本分类方法 |
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| 引用本文： | 魏程,刘鲁,翟铭.一种四维向量空间模型的Web新闻文本分类方法[J].微计算机应用,2010,31(3). |
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| 作者姓名： | 魏程 刘鲁 翟铭 |
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| 作者单位： | 1. 北京航空航天大学,经济管理学院,北京,100191
2. 北京航空航天大学,自动化及电气工程学院,北京,100191 |
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| 摘 要： | 文本分类研究逐渐成为网络文本挖掘的研究热点,针对中文文本进行自动分类的研究也在逐渐升温.针对新闻文本的特殊性,在文本分类中经典的向量空间模型的基础上,提出了一套改进的四维向量空间模型及自适应追踪策略,进而提高了新闻文本分类的效果.实验结果表明,算法可以使传统空间向量模型的分类性能由81.5%提高至92.49%,证明算法是有效的.
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| 关 键 词： | 文本挖掘 文本分类 向量空间模型 四维向量空间模型 |
A Method for Web News-Text Classification with Four-dimensional Vector Space Model |
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| WEI Cheng,LIU Lu,ZHAI Ming.A Method for Web News-Text Classification with Four-dimensional Vector Space Model[J].Microcomputer Applications,2010,31(3). |
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| Authors: | WEI Cheng LIU Lu ZHAI Ming |
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| Affiliation: | WEI Cheng1,LIU Lu2,ZHAI Ming3(1Beihang University School of Economic , Management,Beijing,100191,China2Beihang University School of Automation , Electrical Engineering,China) |
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| Abstract: | Web-page classification has become a hot spot in the fields of Web Text Mining in recent years. Research in Chinese text automatic classification is gradually warming. In this paper, we have put forward a four-dimensional vector space model which is based on the classic vector space model, and have improved the adaptive methods. Experimental results show that the proposed method can improve the effectiveness of classification from 81.5% to 92.49%, which prove that the method is effective. |
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| Keywords: | text mining text classification vector space model four-dimensional vector space model |
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