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- This paper applies BVM to text categorization. 本文将BVM应用于文本分类。
- 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。
- 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.
- This system can elevate the efficiency of information analysis,literature research, text categorization and data mining analysis. 这一处理过程能够帮助研究者提高文献信息的获取效率,并且为进一步的文献研究工作、文本分类、挖掘分析等提供完善、科学、可靠的信息及数据来源。
- On the basis of immune algorithm, the authors propose a new method of text categorization called clonal selection algorithm based on antibody density. 借鉴了免疫系统的分类本质以及免疫系统的克隆选择和抗体浓度控制原理,提出了基于抗体浓度的克隆选择算法。
- In this paper,a flexible KNN algorithm is developed with varying-K algorithm and weighting algorithm,which improves the effect of text categorization. 基于近邻序列的排序,提出了变K算法,并且结合效果较好权重算法,形成了柔性的KNN算法,提高了分类的效果。
- A text categorization test is conducted to compare our method with other several classification methods, and one will see that ours outperforms them. 文本分类的实验结果表明，与其它几个分类算法相比，它具有较高的性能。
