Frequent term-based text clustering [2] is a recently introduced text clustering technique, which uses frequent term sets and dramatically decreases the dimensionality of the document vector space, thus especially addressing itself to the problems of text clustering: very high dimensionality of the date and very large size of the databases [2]. Moreover, frequent term sets provide understandabl...

In this paper the problems of deriving a taxonomy from a text and concept-oriented text segmentation are approached. Formal Concept Analysis (FCA) method is applied to solve both of these linguistic problems. The proposed segmentation method offers a conceptual view for text segmentation, using a context-driven clustering of sentences. The Concept-oriented Clustering Segmentation algorithm (COC...