Study on Chinese text clustering models in compliance with the characteristics of Chinese texts.
针对中文文本组成上的特点，研究了中文文本聚类的模型。
As an exploratory data analysis method, text clustering is very important in text mining.
文本聚类是目前文本挖掘中重要的探索性数据分析方法。
In text classification, we advance an automatic text classification way based on clustering and Rough Set Theory.
在文本分类方面，本文提出了一种基于聚类和粗糙集理论相结合的文本自动分类方法。
Experiment results indicate that the proposed algorithm outperforms the existing text clustering algorithms in accuracy.
实验表明，该算法与现有的文本聚类算法相比，准确率有一定的提高。
In the domain of information retrieval, using feature clustering to extract the features is one of the most important means in the reduction of text dimension.
借助特征聚类进行特征抽取是信息检索领域进行文本特征降维的重要手段之一。
Text clustering is an important research branch of clustering method and it is the application of clustering method used in text processing field.
文本聚类是聚类分析领域的一个重要研究分支，是聚类方法在文本处理领域的重要应用。
Several methods of data mining and text mining have been studied in this paper, which mainly includes: attribute reduction methods, clustering methods.
本文研究了基于遗传算法和社会演化算法的数据挖掘和文本挖掘方法，主要包括数据挖掘和文本挖掘中的属性约简问题、聚类问题。
The proposed method is able to locate obvious text areas in images accurately. But for drawbacks of clustering and immature features, it can't locate background-like and skewed text.
本文提出的基于连通组件的文字定位方法可以非常好地定位出图像中的显著文字区域，但是由于聚类和使用的特征不够完善，不能定位与背景色相近或者是倾斜的文字。
Currently, common text clustering methods are based on document content, in which global document information is needed.
目前，常见的文本聚类都是基于文档内容的，通常需要获得全局的文档信息。
Currently, common text clustering methods are based on document content, in which global document information is needed.
目前，常见的文本聚类都是基于文档内容的，通常需要获得全局的文档信息。
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