使用混合算法的Web分类

Wei-guo Ye, Zheng-ding Lu
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引用次数: 0

摘要

如今,从网上获取信息已成为一个非常重要的问题。传统的文本分类算法已不能满足web分类的需要。本文讨论了Web分类的过程,提出了一种新的特征选择和术语加权的信息增益度量。我们还讨论了三种线性分类器。然后,我们提出了一种新的基于超链接的分类器。它利用了Web图的特点。实验结果表明,该方法比传统的信息检索方法更适合Web分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Web categorization using hybrid algorithms
Obtaining information from the Web is becoming a very much important issue nowadays. The traditional text categorization algorithm is not sufficient for web categorization. In this paper we discuss the process in Web categorization, and proposed a new information gain measure for feature selections and term weighting. We also discussed three linear classifiers. Then we propose a novel hyperlink based classifier. It uses the characteristics of the Web graph. Experimental comparisons of these algorithms show that our approach is more appropriate than traditional information retrieval methods in Web categorization.
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