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Answer Extraction from Technical Texts


Aliod Moll, D; Rinaldi, F; Schwitter, R; Dowdall, J; Hess, M (2003). Answer Extraction from Technical Texts. IEEE Intelligent Systems, 18(4):12-17.

Abstract

For most companies and organizations, technical documents are highly valued knowledge sources because they combine the know-how and experience of specialists in a particular domain. To guarantee the optimal use of these documents in specific problem situations, people must be able to quickly find precise and highly reliable information. Answer extraction is a new technology that helps users find precise answers to their questions in technical documents. In this article, the authors present ExtrAns, a real-world answer extraction system designed for technical domains. ExtrAns uses robust natural language processing technology and a semantic representation for information's propositional content. Knowing the forms of a domain's terminology and understanding the relation between the terms is vital for answer extraction. By applying rewrite rules in a systematic way, ExtrAns gets a grip on technical terminology.

For most companies and organizations, technical documents are highly valued knowledge sources because they combine the know-how and experience of specialists in a particular domain. To guarantee the optimal use of these documents in specific problem situations, people must be able to quickly find precise and highly reliable information. Answer extraction is a new technology that helps users find precise answers to their questions in technical documents. In this article, the authors present ExtrAns, a real-world answer extraction system designed for technical domains. ExtrAns uses robust natural language processing technology and a semantic representation for information's propositional content. Knowing the forms of a domain's terminology and understanding the relation between the terms is vital for answer extraction. By applying rewrite rules in a systematic way, ExtrAns gets a grip on technical terminology.

Citations

4 citations in Web of Science®
7 citations in Scopus®
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Date:2003
Deposited On:13 Jun 2009 13:12
Last Modified:05 Apr 2016 13:15
Publisher:UNSPECIFIED
Additional Information:© 2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE
Publisher DOI:https://doi.org/10.1109/MIS.2003.1217623
Permanent URL: https://doi.org/10.5167/uzh-19110

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