| Title |
Extraction of Semantic Clusters for Terminological Information Retrieval from MRDs |
| Authors |
Sierra Gerardo (Instituto de Ingeniería, UNAM Apdo. Postal 70-472 México 04510, D.F., email: gsm@pumas.iingen.unam.mx)
McNaught John (Centre for Computational Linguistics, UMIST P.O.Box 88 Manchester, U.K., M60 1QD email: jock@ccl.umist.ac.uk) |
| Keywords |
Clustering, Definitions, Dictionaries, Information Retrieval, Lexicography, Natural Language Processing, Ontologies, Semantics, Terminology |
| Session |
Session TP1 - Terminology |
| Full Paper |
35.ps, 35.pdf |
| Abstract |
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. |
