A detailed design and implementation of a Chinese Web-page classification system is introduced, and some methods on Web-page preprocessing and feature processing are proposed.
本文详细介绍了一个中文网页分类系统的设计与实现，并且提出了一些网页预处理和特征处理的方法。
Web page classification was one of the hot study problems in the domain of Internet Search currently. Now there were the classifiers based on text and the hyperlinks.
网页自动分类是当前互联网搜索领域一个热点研究课题，目前主要有基于网页文本内容的分类和基于网页间超链接结构的分类。
The WAS generally includes the Web page purification, feature selection, vector representation, training algorithm, classification al.
网页自动分类一般包括网页净化、特征选择、向量表示、训练算法、分类算法等五个部分。
Secondly, the system can distinguish the domain of the web page and understand the document at the concept level by text classification, clustering and concept extraction based machine learning.
其次，采用机器学习技术，包括文本分类、聚类，文本概念抽取，从概念层次理解文本信息；
WEB page content structure is very helpful for applications such as information retrieval, classification, information extraction etc.
页面内容结构分析在WEB信息检索、分类和抽取等方面有重要作用。
This is a web page of Classification and Secondary Structure Prediction of Membrane Proteins.
这是膜蛋白分类和二级结构预测在线工具的网页。
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。
This study can be used in network information retrieve, information filter, Chinese text automatic classification, Chinese web page automatic classification and other application fields.
该研究可应用于网络信息检索、信息过滤、中文文本自动分类、中文网页自动分类等应用领域。
Some key technology of this model is introduced, such as model's work principle and identify of user, classification of web page.
介绍了模型中的一些关键技术，如模型工作原理、用户标识确定、访问资源分类、客户端浏览行为获取等。
This paper presented a Web page classification model based on Support Vector Machine(SVM)concerning the widely used asynchronous communication technology today.
该模型根据异步通信技术反映在页面上的特点，确定特征向量元素，结合SVM分类算法，建立基于SVM的页面分类。
Due to the needs of automatization and intellectualization of browser, we design and implement a browser with the function of Web page classification.
从浏览器的自动化和智能化出发，设计并实现了一个具有网页自动分类功能的浏览器。
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。
On this basis, we propose a hierarchical model of text classification, then this model is applied to the Chinese web page classification, and we design and implement a prototype system.
在此基础上，本文提出了一个层次式文本分类模型，然后将此模型应用到中文网页分类这一实际问题中，设计并实现了一个原型系统。
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。
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。
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