A Web Document Classification Approach Based on Fuzzy Association Concept

机译：基于模糊关联概念的Web文档分类方法

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In this paper, a method of automatically identifying topics for Web documents via a classification technique is proposed. Web documents tend to have unpredictable characteristics, i.e. differences in length, quality and authorship. Motivated by these fuzzy characteristics, we adopt the fuzzy association concept to classify the documents into some predefined categories or topics. The experimental results show that our approach yields higher classification accuracy compared to the vector space model.

机译：本文提出了一种通过分类技术自动识别Web文档主题的方法。网络文档往往具有不可预测的特征，即长度，质量和作者身份上的差异。受这些模糊特征的影响，我们采用模糊关联概念将文档分类为一些预定义的类别或主题。实验结果表明，与向量空间模型相比，我们的方法具有更高的分类精度。

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来源
《International Conference on Fuzzy Systems and Knowledge Discovery(FSKD 2005) pt.1; 20050827-29; Changsha(CN)》|2005年|P.388-391|共4页
会议地点 Changsha(CN)
作者
Jingsheng Lei; Yaohong Kang; Chunyan Lu; Zhang Yan;
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作者单位

College of Information Science and Technology, Hainan University, Haikou 570228, P.R. China;

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原文格式 PDF
正文语种 eng
中图分类专家系统、知识工程;
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机译：基于模糊关联的Web文档分类

A Web Document Classification Approach Based on Fuzzy Association Concept

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