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A Genetic Fuzzy Automatic Text Summarizer

Daniel LeiteLúcia H. M. Rino

In this paper we report on a fuzzy-based ranking system for selecting sentences for extractive summarization. The fuzzy knowledge base was automatically generated through a genetic algorithm. A corpus of newswire texts and their corresponding manual summaries was used to generate fuzzy classification rules. ROUGE informativeness measure was adopted as the fitness function of such an algorithm.

http://www.lbd.dcc.ufmg.br/colecoes/enia/2009/016.pdf

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