2017/03/19 by Elvys Linhares Pontes, Pontes, Elvys Linhares, Thiago Gouveia da Silva +7
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #cs.CL
paper · pdf · doi:10.48550/arxiv.1703.06501
12 pages, 1 figure, 3 tables (paper in Portuguese), Preprint of XLVIII Simpósio Brasileiro de Pesquisa Operacional, 2016, Vitória, ES, (Brazil)
arxiv created 2017/03/19 · arxiv updated 2017/03/21
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.