LREC 2000 - Papers

LREC 2000 2^nd International Conference on Language Resources & Evaluation

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Title Creating and Using Domain-specific Ontologies for Terminological Applications

Authors Maynard Diana (Dept. of Computer Science, Sheffield University, Regent Court, 211 Portobello Rd, Sheffield S1 4DP, U.K., D.Maynard@dcs.shef.ac.uk)
Ananiadou Sophia (Computer Science, School of Sciences, University of Salford, Newton Building, Salford, M5 4WT, U.K., S.Ananiadou@salford.ac.uk)

Keywords Lexical Resources, NLP, Ontology, Terminology

Session Session TO1 - Terminology

Abstract Huge volumes of scientific databases and text collections are constantly becoming available, but their usefulness is at present hampered by their lack of uniformity and structure. There is therefore an overwhelming need for tools to facilitate the processing and discovery of technical terminology, in order to make processing of these resources more efficient. Both NLP and statistical techniques can provide such tools, but they would benefit greatly from the availability of suitable lexical resources. While information resources do exist in some areas of terminology, these are not designed for linguistic use. In this paper, we investigate how one such resource, the UMLS, is used for terminological acquisition in the TRUCKS system, and how other domain-specific resources might be adapted or created for terminological applications.

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Title	Creating and Using Domain-specific Ontologies for Terminological Applications
Authors	Maynard Diana (Dept. of Computer Science, Sheffield University, Regent Court, 211 Portobello Rd, Sheffield S1 4DP, U.K., D.Maynard@dcs.shef.ac.uk) Ananiadou Sophia (Computer Science, School of Sciences, University of Salford, Newton Building, Salford, M5 4WT, U.K., S.Ananiadou@salford.ac.uk)
Keywords	Lexical Resources, NLP, Ontology, Terminology
Session	Session TO1 - Terminology
Abstract	Huge volumes of scientific databases and text collections are constantly becoming available, but their usefulness is at present hampered by their lack of uniformity and structure. There is therefore an overwhelming need for tools to facilitate the processing and discovery of technical terminology, in order to make processing of these resources more efficient. Both NLP and statistical techniques can provide such tools, but they would benefit greatly from the availability of suitable lexical resources. While information resources do exist in some areas of terminology, these are not designed for linguistic use. In this paper, we investigate how one such resource, the UMLS, is used for terminological acquisition in the TRUCKS system, and how other domain-specific resources might be adapted or created for terminological applications.