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Answer Extraction in Technical Domains

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Computational Linguistics and Intelligent Text Processing (CICLing 2002)

Abstract

In recent years, the information overload caused by the new media has made the shortcomings of traditional Information Retrieval increasingly evident. Practical needs of industry, government organizations and individual users alike push the research community towards systems that can exactly pinpoint those parts of documents that contain the information requested, rather than return a set of relevant documents. Answer Extraction (AE) systems aim to satisfy this need. In this article we discuss the problems faced in AE and present one such system.

It has been often observed that traditional Information Retrieval should rather be called “Document Retrieval”.

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Rinaldi, F. et al. (2002). Answer Extraction in Technical Domains. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2002. Lecture Notes in Computer Science, vol 2276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45715-1_37

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  • DOI: https://doi.org/10.1007/3-540-45715-1_37

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  • Print ISBN: 978-3-540-43219-7

  • Online ISBN: 978-3-540-45715-2

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