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arXiv · 0905.2990

Automatic Summarization System coupled with a Question-Answering System (QAAS)

Juan-Manuel Torres-Moreno·Pier-Luc St-Onge·Michel Gagnon·Marc El-Bèze·Patrice Bellot
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Abstract

To select the most relevant sentences of a document, it uses an optimal decision algorithm that combines several metrics. The metrics processes, weighting and extract pertinence sentences by statistical and informational algorithms. This technique might improve a Question-Answering system, whose function is to provide an exact answer to a question in natural language. In this paper, we present the results obtained by coupling the Cortex summarizer with a Question-Answering system (QAAS). Two configurations have been evaluated. In the first one, a low compression level is selected and the summarization system is only used as a noise filter. In the second configuration, the system actually functions as a summarizer, with a very high level of compression. Our results on French corpus demonstrate that the coupling of Automatic Summarization system with a Question-Answering system is promising. Then the system has been adapted to generate a customized summary depending on the specific question. Tests on a french multi-document corpus have been realized, and the personalized QAAS system obtains the best performances.

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Juan-Manuel Torres-Moreno, Pier-Luc St-Onge, Michel Gagnon, Marc El-Bèze, Patrice Bellot. 2009-05-18. Automatic Summarization System coupled with a Question-Answering System (QAAS). https://arxiv.org/abs/0905.2990

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