文本自动分类系统的研究与实现

利用贝叶斯算法，通过对训练文本的学习，构建了一个文本分类器，从而实现了本文提出的自动分类的目标。贝叶斯分类算法是现在比较流行的方法，它的分类效果比较好，简单而且高效，可以通过大规模的训练语料提高分类的质量。文本的分类是选择最有可能生成该文本的类。只有建立了知识库，分类进行训练，才可以构造相应的分类器，对相关的文本进行分类。

The investigation and implement of automatic text classification

We build Bayes classifier to learn knowledge from the records. The classifier realizes the automatic classifying. This method is general and effective. And, the performance will be improved by enlargement of training data. Bayes classifier is the simplest one of these models. The parameters of the model are trained in the data we gathered under independent assumption. The most likely category of the new example is selected with Bayes model rule.