Métodos de Otimização Combinatória Aplicados ao Problema de Compressão MultiFrases

The Internet has led to a dramatic increase in the amount of available information. In this context, reading and understanding this flow of information have become costly tasks. In the last years, to assist people to understand textual data, various Natural Language Processing (NLP) applications bas...

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Bibliographic Details
Published in:arXiv.org 2017-03
Main Authors: Elvys Linhares Pontes, Thiago Gouveia da Silva, Andréa Carneiro Linhares, Torres-Moreno, Juan-Manuel, Huet, Stéphane
Format: Article
Language:English
Subjects:
Combinatorial analysis
Graph theory
Information flow
Natural language processing
Optimization
Performance enhancement
Sentences
Online Access:Get full text
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Summary:The Internet has led to a dramatic increase in the amount of available information. In this context, reading and understanding this flow of information have become costly tasks. In the last years, to assist people to understand textual data, various Natural Language Processing (NLP) applications based on Combinatorial Optimization have been devised. However, for Multi-Sentences Compression (MSC), method which reduces the sentence length without removing core information, the insertion of optimization methods requires further study to improve the performance of MSC. This article describes a method for MSC using Combinatorial Optimization and Graph Theory to generate more informative sentences while maintaining their grammaticality. An experiment led on a corpus of 40 clusters of sentences shows that our system has achieved a very good quality and is better than the state-of-the-art.
ISSN:2331-8422