文本聚类(Text clustering)文档聚类主要是依据著名的聚类假设:同类的文档相似度较大，而不同类的文档相似度较小。作为一种无监督的机器学习方法，聚类由于不需要训练过程，以及不需要预先对文档手工标注类别，因此具有一定的灵活性和较高的自动化处理能力，已经成为对文本信息进行有效地组织、摘要和导航的重要手段，为越来越多的研究人员所关注。(Text clustering document clustering is based on the well-known clustering assumption that documents of the same class are more similar than documents of different classes. As an unsupervised machine learning method, clustering has become an important way to organize, summarize and navigate text information effectively, which is paid more and more attention to by more and more researchers because of its flexibility and high automation ability because it does not require the training process and does not require the prior manual marking of documents)