为此，改进了传统KNN算法，将训练文本中相似度大的文本合并，称为一簇，并计算簇的中心向量。

So, the traditional KNN arithmetic, clusters training document with highly overlapping word is improved, central vector of cluster is gained.

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标注文本集合聚类后生成的类簇被称为聚类描述问题。

Document clustering description is a problem of labeling the clustered results of document collection clustering.

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文本聚类，即将给定的文本集合划分为多个簇，从而达到簇内文本的主题相关性，簇间文本的主题无关性的目的。

Document clustering is to separate the document set into groups, in each group the documents are of the same or related topic.

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