| 基于RBF神经网络和关联规则的Web文本分类规则获取方法 |
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| 引用本文： | 李泽峰,王煜. 基于RBF神经网络和关联规则的Web文本分类规则获取方法[J]. 图书情报工作, 2006, 50(10): 90-92 |
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| 作者姓名： | 李泽峰 王煜 |
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| 作者单位： | 河北大学数学与计算机学院 |
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| 摘 要： | 根据互信息、RBF神经网络和关联规则原理，提出了一种抽取WEB文本分类规则的新方法。先根据互信息选择和各类相关程度大的若干词条，然后采用RBF神经网络方法对选择的特征进行进一步提取，得到维数较小的文本特征向量空间。之后再根据挖掘出的关联规则获取WEB文本分类规则，建立文本分类器，在保证了分类精度的前提下抽取出利于理解的文本分类规则。
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| 关 键 词： | 互信息 RBF神经网络 关联规则 |
| 收稿时间： | 2006-01-16 |
| 修稿时间： | 2006-01-162006-02-21 |
The Web Text Categorization Rule Extraction Based on RBF Neural Network and Association Rule |
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| Li Zefeng,Wang Yu. The Web Text Categorization Rule Extraction Based on RBF Neural Network and Association Rule[J]. Library and Information Service, 2006, 50(10): 90-92 |
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| Authors: | Li Zefeng Wang Yu |
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| Affiliation: | 1. School of Management, Tianjin University, Tianjin 300072;2. School of Computer and Mathematics, Hebei University, Baoding 071002 |
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| Abstract: | This paper presents a new method of Web text categorization rule extraction based on the mutual information, RBF neural network and association rule. In this paper, mutual information is proposed to process the feature selections. And RBF neural network is used to make a further extraction for selected features so as to get the text feature vector space with less dimensions. Finally, through mining association rule and founding text classifier, the Web text categorization rules are obtained. |
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| Keywords: | mutual information RBF neural network association rule |
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