Learning Taxonomy for Text Segmentation by Formal Concept Analysis
Computation and Language
2010-10-13 v1
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.
Cite
@article{arxiv.1010.2384,
title = {Learning Taxonomy for Text Segmentation by Formal Concept Analysis},
author = {Mihaiela Lupea and Doina Tatar and Zsuzsana Marian},
journal= {arXiv preprint arXiv:1010.2384},
year = {2010}
}
Comments
Presented at Synasc 2010, Timisoara, Romania