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- Bayes text categorization 贝叶斯文本分类
- This paper applies BVM to text categorization. 本文将BVM应用于文本分类。
- This paper presents a method of automatic text categorization for Chinese Web pages, which mainly includes such models as Chinese Web pages acquirement, Chinese word splitter, feature selection and native Bayes machine learning and classification. 摘要提出了一种中文网页自动分类的方法，主要包括中文网页的自动抓取、中文分词、特征选取、贝叶斯机器学习与分类等功能模块。
- A comparison of event models for Naive Bayes text classification. 如果在监督环境下,即文本的类别已知。
- KNN algorithm is a common and effective text categorization algorithm. KNN算法是一种常用的效果较好的文本分类算法。
- Automatic text categorization is an effective method to increase efficiency and quality of information utilization. 自动文本分类是提高信息利用效率和质量的有效方法。
- Abstract: Text categorization is defined as the task of assigningpre-defined category labels to new documents. 文摘:文本分类是指在给定分类体系下，根据文本的内容自动确定文本类别的过程。
- Stump Network text classifier is compared with naive bayes text classifier and TAN(tree augmented naive bayes) by an experiment. 将该方法与朴素贝叶斯文本分类器和TAN(tree augmented naive bayes)文本分类器进行实验比较。
- The KNN is a simple,valid and non-parameter method applied to WEB text categorization. KNN算法是一种简单、有效、非参数的Web文本分类方法。
- Two methods for text categorization fuzzy rule extraction are presented based on fuzzy decision tree. 本文提出了两种基于模糊决策树的模糊文本分类规则抽取方法。
- Therefore, text categorization algorithm Weighted Association Rules Categorization (WARC) is proposed in this paper. 本文设计和实现的基于规则权重调整的关联规则文本分类算法可有效地解决这一问题。
- Experiments show that LDA can reduce the features in Chinese text categorization system efficiently. 实验证明线性鉴别分析能够对中文文本分类系统中的特征进行有效约减。
- The vectorization of documents affects the speed and accuracy of text categorization greatly. 文档向量化的质量对于文本分类的速度和准确度有着很大的影响。
- We found IG, MI and CHI had poor performance in our test, though they behave well in English text categorization. 实验结果表明，在英文文本分类中表现良好的特徵抽取方法(IG、MI和CHI)在不加修正的情况下并不适合中文文本分类。
- The system can preferably implement automatic text categorization for Chinese pages, and has a higher quality. 该系统可以很好地实现一个中文网页的自动分类，且系统中的分类器具有较高的分类质量。
- Feature extraction is keystone and difficulty of text categorization using machine learning. 特征抽取是用机器学习方法进行文本分类的重点和难点。
- On large amount conditions of text quantity, hierarchical text categorization was an effective approach. 摘要在文本分类的类别数量庞大的情况下，层次分类是一种有效的分类途径。
- 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。
- Text classification feature selection in text categorization is the first important problem to be solved. 摘要文本分类特征选择是文本自动分类中首先要解决的重要问题。
- This paper employs Feedback methods for Text Categorization systems and reduces the need for labeled training documents. 本文通过在文本分类系统中应用反馈方法;大大地减少了系统在训练过程中对训练文档数量的要求.
