Answer extraction in technical domains

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Fabio Rinaldi, Michael Hess, Diego Mollá, Rolf Schwitter, James Dowdall, Gerold Schneider, Rachel Fournier

Published: 01 Jan 2002, Last Modified: 26 May 2026Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)EveryoneRevisionsBibTeXCC BY-SA 4.0
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.