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arXiv · 1010.2384

Learning Taxonomy for Text Segmentation by Formal Concept Analysis

Mihaiela Lupea·Doina Tatar·Zsuzsana Marian
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Abstract

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 (COCS) is based on k-means linear clustering of the sentences. Experimental results obtained using COCS algorithm are presented.

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Mihaiela Lupea, Doina Tatar, Zsuzsana Marian. 2010-10-12. Learning Taxonomy for Text Segmentation by Formal Concept Analysis. https://arxiv.org/abs/1010.2384

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