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Title:      AUTOMATIC SUMMARIZATION OF NEWS USING WORDNET CONCEPT GRAPHS
Author(s):      Laura Plaza , Alberto Díaz , Pablo Gervás
ISBN:      978-972-8924-86-7
Editors:      Hans Weghorn, Jörg Roth and Pedro Isaías
Year:      2009
Edition:      Single
Keywords:      Automatic Summarization, Graph Theory, Ontology, Natural Language Processing
Type:      Full Paper
First Page:      19
Last Page:      26
Language:      English
Cover:      cover          
Full Contents:      click to dowload Download
Paper Abstract:      One of the main handicaps in research on automatic summarization is the vague semantic comprehension of the source, which is reflected in the poor quality of the consequent summaries. Using further knowledge, as that provided by ontologies, to construct a complex semantic representation of the text, can considerably alleviate the problem. In this paper, we introduce an ontology-based extractive method for summarization. It is based on mapping the text to concepts and representing the document and its sentences as graphs. We have applied our approach to news articles, taking advantages of free resources such as WordNet. Preliminary empirical results are presented and pending problems are identified.
   

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