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J. Wu, B.G. Heydecker, "Natural Language Understanding in Road Accident Data Analysis", in B.H.V. Topping, (Editor), "Developments in Artificial Intelligence for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 129-143, 1995. doi:10.4203/ccp.35.8.1

Abstract

Road accident records in Britain comprise two components each: coded data in predefined format, and plain English descriptions in free format. This paper describes a natural language understanding system for information retrieval from the latter to verify and extend the former. We adopt the description logic system BACK to achieve a common representation of information from each of the two sources to facilitate comparison. A sub-category grammar is adapted to achieve automatic classification in BACK, and a bidirectional chart parser is adapted to operate with this grammar. This gives good independence between grammar rules, and provides flexibility, expressiveness, and the ability to resolve ambiguities.

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Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 35 DEVELOPMENTS IN ARTIFICIAL INTELLIGENCE FOR CIVIL AND STRUCTURAL ENGINEERING Edited by: B.H.V. Topping Paper VIII.1 Natural Language Understanding in Road Accident Data Analysis J. Wu and B.G. Heydecker Centre for Transport Studies, University College London, London, UK doi:10.4203/ccp.35.8.1 purchase the full-text of this paper Full Bibliographic Reference for this paper J. Wu, B.G. Heydecker, "Natural Language Understanding in Road Accident Data Analysis", in B.H.V. Topping, (Editor), "Developments in Artificial Intelligence for Civil and Structural Engineering", Civil-Comp Press, Edinburgh, UK, pp 129-143, 1995. doi:10.4203/ccp.35.8.1 Abstract Road accident records in Britain comprise two components each: coded data in predefined format, and plain English descriptions in free format. This paper describes a natural language understanding system for information retrieval from the latter to verify and extend the former. We adopt the description logic system BACK to achieve a common representation of information from each of the two sources to facilitate comparison. A sub-category grammar is adapted to achieve automatic classification in BACK, and a bidirectional chart parser is adapted to operate with this grammar. This gives good independence between grammar rules, and provides flexibility, expressiveness, and the ability to resolve ambiguities. purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £65 +P&P)
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