Text feature selection is a process of recognizing and deleting redundant information and enhancing training documents cluster quality.
文本特征选择是最大程度地识别和去除冗余信息，提高训练数据集质量的过程。
The author gains insights from attribute reduction based on discernability matrix and proposes a few rough-set based text feature selection algorithms, i. e. , DB1, DB2 and LDB.
作者从基于分辨矩阵的粗糙集属性约简中受到启发，提出了一系列基于粗集理论的文本特征选择算法，即DB1、DB2、LDB。
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。
Two important research directions of text classification are: feature selection method and text classification algorithm.
文本分类的两个重要的研究方向是：特征选择与文本分类算法。
In this paper, we will propose a method of feature selection and weighting scheme based on text set density, which is a way of measure of contribution to the text set density about some word.
在这篇论文中，我们提出了一种基于文本集密度的特征词选择与权重计算方案的方法。
Feature selection is frequently used as a preprocessing step to text classification, which is effective in reducing dimensionality and increasing classification accuracy.
特征选择是文档分类中常见的预处理工作，通过对文档特征空间降维，可以提高文档的分类性能。
Text categorization is the foundation of text mining, and feature selection is the core of text categorization.
文本分类是文本挖掘的基础，而特征选择又是文本分类中的核心。
Feature selection is a core research topic in text categorization.
特征选择是文本分类的一个核心研究课题。
To verify efficiency of the new feature selection approach and improved TF-IDF formula, a multi-set of experiments base on the Chinese text categorization test system platform have been taken.
本文在中文文本分类实验平台上，通过多组对比实验来考察本文提出的新的特征提取方法和改进的TF-IDF方法的有效性。
Feature selection has been effectively applied in text classification, because of its simplicity, fast calculation, suitable for handling large-scale text data.
特征提取因其方法简单、计算速度快，适合用来处理大规模的文本数据，在文本分类中得到了广泛的应用。
It used the word as the unit for feature selection and add the pretreatment in text sentiment analysis process.
提出了以词为单位进行特征的选取，并在文本的情感分析中加入了预处理过程。
The text preprocessing, feature selection, training algorithm, and recognition method are described in the paper.
对文本分类系统的系统结构、预处理、特征提取、训练算法、分类算法等进行了详细介绍。
The experimental results are similar using plain English text and Chinese Web pages to evaluate feature selection methods.
使用普通英文文本和中文网页评测特征选取方法的结果是一致的。
The experimental results are similar using plain English text and Chinese Web pages to evaluate feature selection methods.
使用普通英文文本和中文网页评测特征选取方法的结果是一致的。
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