In this paper, a web page classification with feature selection and fuzzy learning is proposed.
本文提出了一种基于相似度的特征选择算法和适应模糊学习算法来实现分类。
Document clustering had been employed in information filtering, web page classification and so on.
文本聚类在信息过滤，网页分类中有着很好的应用。但它面临数据量大，特征维度高的难点。
A new algorithm based on representative samples dynamical generation for Chinese Web page classification was proposed in this paper.
针对中文网页分类问题该文设计了一种新的基于代表样本动态生成的分类算法。
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