A New Hybrid Summarizer Based on Vector Space Model, Statistical Physics and Linguistics

In this article we present a hybrid approach for automatic summarization of Spanish medical texts. There are a lot of systems for automatic summarization using statistics or linguistics, but only a few of them combining both techniques. Our idea is that to reach a good summary we need to use linguistic aspects of texts, but as well we should benefit of the advantages of statistical techniques. We have integrated the Cortex (Vector Space Model) and Enertex (statistical physics) systems coupled with the Yate term extractor, and the Disicosum system (linguistics). We have compared these systems and afterwards we have integrated them in a hybrid approach. Finally, we have applied this hybrid system over a corpora of medical articles and we have evaluated their performances obtaining good results.

• Type: Conference
• Year: 2007
• Where: MICAI
• Authors: Iria da Cunha, Silvia Fernández, Patricia Velázquez-Morales, Jorge Vivaldi, Eric SanJuan, Juan Manuel Torres Moreno
• Keywords: Artificial Intelligence, Automatic Summarization, Hybrid Approach, MICAI 2007, Spanish Medical Texts