本文研究文本的自动分类算法。
This paper mainly focus on the text classification algorithms.
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.
本文利用前向神经网络的交叉覆盖算法，通过对文本进行分词的预处理后，实现文本的自动分类。
Based on the Crossing Cover Algorithm of forward neural network, this paper realizes the automatic classification of texts after the preprocessing of the texts.
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.
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.
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.
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