为了改善文本聚类的准确度，提出用基于主题概念子空间的模糊c -均值聚类(TCS2FCM)方法来分类文本。
To improve the accuracy of text clustering, fuzzy c-means clustering based on topic concept sub-space (TCS2FCM) is introduced for classifying texts.
针对词、潜在概念、文本和主题之间的模糊关系，提出一种基于信息论的潜在概念获取与文本聚类方法。
To emphasize the fuzzy relation among words, latent concepts, text and topics, an information theory based approach to latent concept extraction and text clustering is proposed.
针对词、潜在概念、文本和主题之间的模糊关系，提出一种基于信息论的潜在概念获取与文本聚类方法。
To emphasize the fuzzy relation among words, latent concepts, text and topics, an information theory based approach to latent concept extraction and text clustering is proposed.
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