Title: NewsGist: A Multilingual Statistical News Summarizer
Authors: KABADJOV MIJAILATKINSON MartinSTEINBERGER JOSEFSTEINBERGER RalfVAN DER GOOT Erik
Citation: LECTURE NOTES IN ARTIFICIAL INTELLIGENCE vol. 6323/2010 no. part III p. 491-494
Publisher: SPRINGER-VERLAG BERLIN
Publication Year: 2010
JRC Publication N°: JRC59053
ISSN: 0302-9743
URI: http://publications.jrc.ec.europa.eu/repository/handle/JRC59053
DOI: 10.1007/978-3-642-15939-8_40
Type: Contributions to Conferences
Abstract: In this paper we present NewsGist, a multilingual, multi-document news summarization system underpinned by the Singular Value Decomposition (SVD) paradigm for document summarization and purpose-built for the European Media Monitor. The summarization method employed yielded state-of-the-art performance for English at the Update Summarization task of the last Text Analysis Conference (TAC) 2009 and integrated with EMM represents the first online summarization system able to produce summaries for so many languages (50+). We discuss the context and motivation for developing the system and provide an overview of its architecture. The paper is intended to serve as accompaniment of a live demo of the system, which can be of interest to researchers and engineers working on multilingual open-source news analysis and mining.
JRC Institute:Institute for the Protection and Security of the Citizen

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