A Two-level Text Classification Based on Feature Extraction

Zou Li-na; Ling Jie

doi:10.3969/j.issn.1007-7162.2012.04.013

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A Two-level Text Classification Based on Feature Extraction

更新时间：2026-05-27

- A Two-level Text Classification Based on Feature Extraction
- Vol. 29, Issue 4, Pages: 65-68(2012)
- 作者机构：
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- DOI：10.3969/j.issn.1007-7162.2012.04.013
  CLC：
- Online First：25 December 2012，
  
  Published：2012
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邹丽娜, 凌捷. 一种基于特征提取的二级文本分类方法[J]. 广东工业大学学报, 2012, 29(4): 65-68.

Zou Li-na, Ling Jie. A Two-level Text Classification Based on Feature Extraction[J]. 2012, 29(4): 65-68.
邹丽娜, 凌捷. 一种基于特征提取的二级文本分类方法[J]. 广东工业大学学报, 2012, 29(4): 65-68. DOI： 10.3969/j.issn.1007-7162.2012.04.013.

Zou Li-na, Ling Jie. A Two-level Text Classification Based on Feature Extraction[J]. 2012, 29(4): 65-68. DOI： 10.3969/j.issn.1007-7162.2012.04.013.

摘要

提出了一种改进的基于特征提取的二级文本分类方法.通过提取出文本的特征项并计算其权重值，将文本表示成由特征项和权重值组成的向量，利用向量的夹角余弦计算二级分类模型下文本之间的相似度，可以更准确快速地定位海量信息.实验结果表明本文提出的分类方法的准确率优于传统的类中心分类法，提高了系统的适应性和分类能力.

Abstract

An improved two-level text classification method is proposed

based on feature extraction. First

the characteristics of the text were extracted

and the weights were calculated. Then

the text was represented as a vector composed of characteristics and weight value. The vector angle cosine was used to calculate the similarity among the text so as to position the vast amount of information more accurately and rapidly. The experimental results show that the proposed classification method is superior to the existing center classification method in accuracy of classification

improving the adaptability and classification ability of the system.

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