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Aspects of Multilingual News Summarisation

Aspects of Multilingual News Summarisation

Josef Steinberger, Ralf Steinberger, Hristo Tanev, Vanni Zavarella, Marco Turchi
Copyright: © 2014 |Pages: 18
ISBN13: 9781466650190|ISBN10: 1466650192|EISBN13: 9781466650206
DOI: 10.4018/978-1-4666-5019-0.ch012
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MLA

Steinberger, Josef, et al. "Aspects of Multilingual News Summarisation." Innovative Document Summarization Techniques: Revolutionizing Knowledge Understanding, edited by Alessandro Fiori, IGI Global, 2014, pp. 277-294. https://doi.org/10.4018/978-1-4666-5019-0.ch012

APA

Steinberger, J., Steinberger, R., Tanev, H., Zavarella, V., & Turchi, M. (2014). Aspects of Multilingual News Summarisation. In A. Fiori (Ed.), Innovative Document Summarization Techniques: Revolutionizing Knowledge Understanding (pp. 277-294). IGI Global. https://doi.org/10.4018/978-1-4666-5019-0.ch012

Chicago

Steinberger, Josef, et al. "Aspects of Multilingual News Summarisation." In Innovative Document Summarization Techniques: Revolutionizing Knowledge Understanding, edited by Alessandro Fiori, 277-294. Hershey, PA: IGI Global, 2014. https://doi.org/10.4018/978-1-4666-5019-0.ch012

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Abstract

In this chapter, the authors discuss several pertinent aspects of an automatic system that generates summaries in multiple languages for sets of topic-related news articles (multilingual multi-document summarisation), gathered by news aggregation systems. The discussion follows a framework based on Latent Semantic Analysis (LSA) because LSA was shown to be a high-performing method across many different languages. Starting from a sentence-extractive approach, the authors show how domain-specific aspects can be used and how a compression and paraphrasing method can be plugged in. They also discuss the challenging problem of summarisation evaluation in different languages. In particular, the authors describe two approaches: the first uses a parallel corpus and the second statistical machine translation.

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