NewsGist: A Multilingual Statistical News Summarizer
- Cite this paper as:
- Kabadjov M., Atkinson M., Steinberger J., Steinberger R., van der Goot E. (2010) NewsGist: A Multilingual Statistical News Summarizer. In: Balcázar J.L., Bonchi F., Gionis A., Sebag M. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2010. Lecture Notes in Computer Science, vol 6323. Springer, Berlin, Heidelberg
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 Europe Media Monitor (EMM). 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. 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.
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