This paper applies BVM to text categorization.
本文将BVM应用于文本分类。
This approach can increase the accuracy of text categorization.
该方法能够有效地提高分类的准确度。
KNN algorithm is a common and effective text categorization algorithm.
KNN算法是一种常用的效果较好的文本分类算法。
High dimensionality is one of the main problems in text categorization.
文本分类中特征空间的高维问题是文本分类的主要障碍之一。
Text categorization is one of the important techniques in textual data mining.
文本分类是文本数据挖掘的重要技术。
Constructing an effective text classifier plays a key role in text categorization.
构建一个分类准确的文本分类器是文本分类的关键。
Text Categorization(TC) is a technique of assigning a document into predefined class.
文本分类，是一种对文档进行自动标记类别的技术。
This paper presents some research on automatic Chinese text categorization system (CATCS).
本文就中文自动文本分类系统进行了一些研究。
Reducing the high dimension of feature vectors is an essential part of text categorization.
对高维的特征集进行降维是文本分类过程中的一个重要环节。
The main deducing steps are presented in the core-training algorithm of text categorization.
对于文本分类的核心训练算法，给出主要步骤的推导过程；
The vectorization of documents affects the speed and accuracy of text categorization greatly.
文档向量化的质量对于文本分类的速度和准确度有着很大的影响。
The most important issue in text categorization is mathematical expression model of text data.
文本开类的沉要题纲非文本数据的数教外示模型。
Text categorization is defined as the task of assigning pre-defined category label to a new text.
文本分类是指在给定分类体系下，根据文本的内容自动确定文本类型的过程。
With the increasing of text databases, it is urgent to find out a new method of text categorization.
随着文本数据库的日益增大，寻找新的文本数据处理方法变得十分紧迫。
On large amount conditions of text quantity, hierarchical text categorization was an effective approach.
在文本分类的类别数量庞大的情况下，层次分类是一种有效的分类途径。
To solve the problems mentioned before, semantic dictionary was led into the domain of text categorization.
为懂得决上述题纲，本文将语义词典引入到文本开类范畴。
Text categorization is an important task in Data Mining, and it is an important way for getting information.
文本分类是数据挖掘的重要课题，它是获取信息资源的重要方式之一。
The system can preferably implement automatic text categorization for Chinese pages, and has a higher quality.
该系统可以很好地实现一个中文网页的自动分类，且系统中的分类器具有较高的分类质量。
Feature selection is a valid method to reduce the dimension of text vector in automatic text categorization system.
在自动文本分类系统中，特征选择是有效降低文本向量维数的一种方法。
In this article we discussed filter spam methods using text categorization technologies in machine learning fields.
本文使用机器学习理论，讨论了用文本分类的方法来过滤垃圾邮件。
A reduction algorithm based on rough set is improved and then applicated to extract the rules of text categorization.
改进了一种粗糙集决策表的值约简算法，并将其应用到文本分类规则的提取中。
After the overall analysis, this paper proposed a new algorithms for page ranking, which is based on Text Categorization.
在对这些因素进行分析之后，本文提出了一种基于文本分类的网页排序算法。
This paper proposes an example based mapping method, which USES Chinese properties of CCs for Chinese text categorization.
本文提出了一种根据汉字统计特性和基于实例映射的中文文本自动分类模型。
The text categorization has become a hot research subject which has attracted a lot of attention but still not solved well.
文本分类成为众所关注但仍未很好解决的热门课题。
Text Categorization means under a defined classifying system, texts are classified automatically according to the contents.
文本分类是指在给定的分类体系下，根据文本的内容自动地确定文本所属的类别。
Text feature extraction and text categorization is the focal point of basic research in the field of intelligent information service system.
文本信息特征提取和文本分类是当前智能信息服务系统基础研究的重点。
This paper presents a new method of WEB text categorization rule extraction based on the CHI value theory, rough set theory and decision tree.
本文根据CHI值原理、粗集理论和决策树原理，提出了一种抽取Web文本分类规则的新方法。
Text categorization and feature concept extraction is the focal point of basic research in the field of intelligent information service system.
文本分类与文本信息特征概念的提取是当前智能信息服务研究的重点。
Text categorization and feature concept extraction is the focal point of basic research in the field of intelligent information service system.
文本分类与文本信息特征概念的提取是当前智能信息服务研究的重点。
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