LDE and simplified SVM method for document classification

doi:10.3778/j.issn.1002-8331.2009.22.001

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (22): 1-3.DOI: 10.3778/j.issn.1002-8331.2009.22.001

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LDE and simplified SVM method for document classification

WANG Zi-qiang¹，QIAN Xu¹，KONG Min²

1.College of Mechanical Electronic and Info. Eng.，China University of Mining and Technology（Beijing），Beijing 100083，China
2.Qufu Vocational School of Shandong Province，Qufu，Shandong 273100，China

Received:2009-04-15 Revised:2009-05-18 Online:2009-08-01 Published:2009-08-01
Contact: WANG Zi-qiang

面向文档分类的LDE和简化SVM方法研究

王自强¹，钱旭¹，孔敏²

1.中国矿业大学（北京）机电与信息工程学院，北京 100083
2.山东省曲阜市职业中等专业学校，山东曲阜 273100

通讯作者: 王自强

Abstract

Abstract: To rapidly and accurately perform document classification task，an efficient document classification algorithm is proposed by using Local Discriminant Embedding（LDE） and Simplified Support Vector Machine（SSVM） in this paper.The essential idea of the algorithm is as follows.The high dimensional document data are first projected into the lower dimensional feature space with LDE algorithm，then the SSVM algorithm is applied to classify documents in the lower dimensional feature space.Experimental results show that the proposed algorithm is of higher classification accuracy and faster running speed.

Key words: document classification, local discriminant embedding, simplified support vector machine, data mining

摘要： 为了快速准确地对文档进行分类，提出了一种基于局部鉴别嵌入LDE和简化SVM的高效文档分类算法。该算法首先利用LDE算法把高维文档数据投影到低维特征空间，然后在低维特征空间利用精简SVM进行分类。实验结果表明该算法具有分类准确率高和运行速度快的优点。

关键词: 文档分类, 局部鉴别嵌入, 简化支持向量机, 数据挖掘

WANG Zi-qiang¹，QIAN Xu¹，KONG Min²

. LDE and simplified SVM method for document classification[J]. Computer Engineering and Applications, 2009, 45(22): 1-3.

王自强¹，钱旭¹，孔敏²

. 面向文档分类的LDE和简化SVM方法研究[J]. 计算机工程与应用, 2009, 45(22): 1-3.

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LDE and simplified SVM method for document classification

面向文档分类的LDE和简化SVM方法研究

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