文本自动分类系统是信息处理的重要研究方向。
The text categorization system is an important research aspect of information processing.
提出了一种基于投影寻踪回归的文本自动分类模型。
This paper presents an automated text classification model based on projection pursuit regression.
文章研究并改进了文本自动分类中的特征权重算法。
This article aims to improve the algorithm of term weighting in automated text classification.
为此，设计一个基于神经网络的文本自动分类系统。
Therefore, designs a text automatic sorting system based on the neural network.
本文的工作是设计并实现一个蒙文文本自动分类器。
This work is to design an automatic classifier of the Mongolian language and bring to bear it.
研究哈萨克语自动文本分类，并实现哈萨克语文本自动分类系统。
Researches on automatic text classification in Kazakh and develops a system of automatic text classification for Kazakh.
本文主要是应用统计的方法对文本自动分类进行理论和实践的探讨。
This paper gives details to the research on the theory and practice of the text automatic classification using the statistical method.
文本自动分类在文献检索、信息过滤和文本管理等领域中有着广泛的应用。
Text automatic classification is widely applied in paper index, message filter, text management and etc.
使用文本自动分类系统可以帮助人们自动检索文本，以及判断文本的类别。
Automatic text classification systems can be used to help people automatically retrieve the text, and determine the type of text.
文本自动分类是指将文本按照一定的策略归于一个或多个类别中的应用技术。
The technique of text automatic category is to classify texts into one or more classes according to some strategy.
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。
This paper proposes an example based mapping method, which USES Chinese properties of CCs for Chinese text categorization.
该研究可应用于信息检索、信息过滤、文本自动分类、网页自动分类等应用领域。
The research can be applied in information retrieval, information filtering, text classification, webpage classification, etc.
文本自动分类方法是指在给定的分类体系下，根据文本的内容自动判别类型的过程。
Text auto-categorization is a process of text auto-differentiation under a given condition.
对文本进行有效管理的方法之一，就是将它们进行系统地分类，即文本自动分类问题。
One method of managing the texts efficiently is to classify them, namely, the problem of text Classification.
在文本分类方面，本文提出了一种基于聚类和粗糙集理论相结合的文本自动分类方法。
In text classification, we advance an automatic text classification way based on clustering and Rough Set Theory.
目前，支持向量机在模式识别、函数逼近、数据挖掘和文本自动分类中均有很好的应用。
Recently, Support Vector Machine is well applied in pattern recognition, function approximate, data mining and text auto categorization.
文本自动分类是在给定的分类体系下，让计算机根据文本的内容确定与它相关联的类别。
Automatic text classification is defined as the task to assign pre-defined category labels to documents.
针对文本自动分类问题，提出了一种基于模糊向量空间模型和径向基函数网络的分类方法。
Aimed at the problems of document automatic classification, a classification method is proposed based on fuzzy vector space model and RBF network.
以该算法为基础，设计了一个英文文本自动分类系统，并对该系统进行了测试和结果分析。
Based on this algorithm, an automatic English text classifier was designed, and the system test and result analysis were made.
本文将粗糙集理论应用于文本自动分类的规则提取，提出了基于粗糙集理论的文本分类方法。
In this paper, a method of text categorization based on rough set theory is presented. RST is applied to rules' extraction of the text categorization.
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。
This study can be used in network information retrieve, information filter, Chinese text automatic classification, Chinese web page automatic classification and other application fields.
该文方法克服了传统IDF方法缺点，能有效地从概念上提取文本类特征，提高文本自动分类的准确性。
This new method eliminates the drawbacks of traditional IDF method and it can efficiently conduct text feature extraction thus to promote the accuracy of automation text categorization.
本文介绍了文本自动分类的研究方法，文本的向量空间模型表示。并给出了文档的训练算法和分类算法。
It introduces the method of the text auto-categorization, briefly describes the vector space model expression, and finally gives training arithmetic and categorization arithmetic of the text.
为了让集合使用自动分类器，需要将集合与新的文本分析引擎关联起来。
To have the collection use the auto-classifier, it needs to be associated with the new text analysis engine.
其他方式依赖于自动文本分类技术。
文本倾向性识别在信息过滤、自动文摘、文本分类等领域有广泛的应用前景。
Text orientation recognition has broad application in some field such as information filtering, automatic abstracting and text classification.
本文在国家科学数字图书馆的应用背景下，研究基于统计的自动文本分类方法。
This article studies the statistical automatic text classification methods in the National Science Digital Library.
电子文档的飞速增长为自动文本分类提供了巨大的机遇和挑战。
The rapid growth in the amount of electronic documents brings both great opportunities and real challenges for automatic text classification.
电子文档的飞速增长为自动文本分类提供了巨大的机遇和挑战。
The rapid growth in the amount of electronic documents brings both great opportunities and real challenges for automatic text classification.
应用推荐