Automatic Summarization System coupled with a Question-Answering System (QAAS)
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.
Keywords
Cite
@article{arxiv.0905.2990,
title = {Automatic Summarization System coupled with a Question-Answering System (QAAS)},
author = {Juan-Manuel Torres-Moreno and Pier-Luc St-Onge and Michel Gagnon and Marc El-Bèze and Patrice Bellot},
journal= {arXiv preprint arXiv:0905.2990},
year = {2009}
}
Comments
28 pages, 11 figures