A Genetic Fuzzy Automatic Text Summarizer - Leite, Daniel; Rino, Lucia H. M. (Anais do Encontro Nacional de Inteligência Artificial e Computacional (ENIAC); 2009: Anais do VII Encontro Nacional de Inteligência Artificial, 2009)
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.