|LREC 2000 2nd International Conference on Language Resources & Evaluation
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|Extraction of Semantic Clusters for Terminological Information Retrieval from MRDs
|Sierra Gerardo (Instituto de Ingeniería, UNAM Apdo. Postal 70-472 México 04510, D.F., email: firstname.lastname@example.org)
McNaught John (Centre for Computational Linguistics, UMIST P.O.Box 88 Manchester, U.K., M60 1QD email: email@example.com)
|Clustering, Definitions, Dictionaries, Information Retrieval, Lexicography, Natural Language Processing, Ontologies, Semantics, Terminology
|Session TP1 - Terminology
|This paper describes a semantic clustering method for data extracted from machine readable dictionaries (MRDs) in order to build a terminological information retrieval system that finds terms from descriptions of concepts. We first examine approaches based on ontologies and statistics, before introducing our analogy-based approach that lets us extract semantic clusters by aligning definitions from two dictionaries. Evaluation of the final set of clusters for a small set of definitions demonstrates the utility of our approach.