基于朴素贝叶斯分类方法的实验表明，提出的方法能够有效提高中文文本的分类准确率。
The experiment of Naive Bayes classification indicates that this method can effectively improve classification precision of Chinese texts.
验证和分析了LSC模型的英文文本和中文文本的分类性能，研究了LSC模型的分类稳定性以及与其它多种分类模型的性能比较问题。
We study the performance of LSC model on English and Chinese corpus respectively, analyze the LSC model's stability, and compare LSC model with some common classification models.
在中文文本分类实验中，可以达到83%的BE P值。
In the experiment of classifying Chinese documents, it is BEP value is about 83%.
本文对中文文本分类的分词技术进行了着重讨论。
In this paper, the Word Segmentation technology of Chinese Text Classification is debated emphatically.
给出一种基于多层前馈神经网络的中文文本分类模型，介绍了该模型的设计和实现。
This paper presents a text categorization model based on multilayered feedforward neutral network, and introduces the design and implementation of this model.
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.
提出了一种基于字特征的中文文本分类方法。
This paper introduces a method on automatic text categorization based on the statistic features of Chinese characters.
介绍了一种基于模糊模式识别以及向量空间模型提取特征向量的中文文本分类器的设计与实现。
This paper introduces the design and implementation of the Chinese text categorizer based on the fuzzy recognition and the extraction of the characteristic vector with the vector space model.
本文提出了一种提高中文文本分类器推广性能的方法。
In the paper, a method to improve the generalization performance of the Chinese text classifier is put forward.
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。
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.
该平台对大多数分类中使用的算法在中文文本分类中的应用效果进行了研究。
Through this platform we studied the performance of most of traditional algorithms when they are now used in Chinese text categorization.
该文针对中文科技论文文本特殊的文体格式和语言风格进行了系统地研究，并提出了基于层次分类模型的文本分类算法。
In this paper, we construct firstly the interval estimates of variance components in the two-way model, depending on corresponding sums of squares from the analysis of variance.
该文针对中文科技论文文本特殊的文体格式和语言风格进行了系统地研究，并提出了基于层次分类模型的文本分类算法。
In this paper, we construct firstly the interval estimates of variance components in the two-way model, depending on corresponding sums of squares from the analysis of variance.
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