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The Internet has led to a dramatic increase in the amount of availableinformation. In this context, reading and understanding this flow ofinformation have become costly tasks. In the last years, to assist people tounderstand textual data, various Natural Language Processing (NLP) applicationsbased on Combinatorial Optimization have been devised. However, forMulti-Sentences Compression (MSC), method which reduces the sentence lengthwithout removing core information, the insertion of optimization methodsrequires further study to improve the performance of MSC. This articledescribes a method for MSC using Combinatorial Optimization and Graph Theory togenerate more informative sentences while maintaining their grammaticality. Anexperiment led on a corpus of 40 clusters of sentences shows that our systemhas achieved a very good quality and is better than the state-of-the-art.

M\'etodos de Otimiza\c{c}\~ao Combinat\'oria Aplicados ao Problema de Compress\~ao MultiFrases