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

Cortex is an automatic generic document summarization system. 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 QuestionAnswering 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 con gurations have been evaluated. In the rst one, a low compression level is selected and the summarization system is only used as a noise lter. In the second con guration, 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 speci c question. Tests on a french multi-document corpus have been realized, and the personalized QAAS system obtains the best performances.