Florian Boudin¹, Stéphane Huet¹, and Juan–Manuel Torres–Moreno²

¹ Universite d'Avignon, France.

² Universite d'Avignon, France; Ecole Polytechnique de Montreal, Canada; Universidad Nacional Autónoma de Mexico, Mexico (e–mail: firstname.lastname@univ–avignon.fr).

Manuscript received November 9, 2010.
Manuscript accepted for publication January 15, 2011.

Abstract

Cross–language summarization is the task of generating a summary in a language different from the language of the source documents. In this paper, we propose a graph–based approach to multi–document summarization that integrates machine translation quality scores in the sentence extraction process. We evaluate our method on a manually translated subset of the DUC 2004 evaluation campaign. Results indicate that our approach improves the readability of the generated summaries without degrading their informativity.

Key words: Graph–based approach, cross–language multi–document summarization.

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