Accès chercheur

EEDIS Laboratory

Evolutionary Engineering

and

Distributed Information Systems

Réseaux et Communication

Sécurité et Multimédia

Ingénierie des Connaissances

Data Mining & Web Intelligent

Interopérabilité des Systèmes d’information
& Bases de données

Développement Orienté Service

Ongoing Developments in Automatically Adapting Lexical Resources to the Biomedical Domain

Auteurs: » Dominic Widdows
» TOUMOUH Adil
» Beate Dorow
» LEHIRECHE AHMED
Type : Conférence Internationale
Nom de la conférence : LREC
Lieu : Pays:
Lien : »
Publié le : 01-05-2006

This paper describes a range of experiments using empirical methods to adapt the WordNet noun ontology for specific use in the biomedical domain. Our basic technique is to extract relationships between terms using the Ohsumed corpus, a large collection of abstracts from PubMed, and to compare the relationships extracted with those that would be expected for medical terms, given the structure of the WordNet ontology. The linguistic methods involve the use of a variety of lexicosyntactic patterns, that enable us to extract pairs of coordinate noun terms, and also related groups of adjectives and nouns, using Markov clustering. This enables us in many cases to analyse ambiguous words and select the correct meaning for the biomedical domain. While results are often encouraging, the paper also highlights evident problems and drawbacks with the method, and outlines suggestions for future work.

Tous droits réservés - © 2019 EEDIS Laboratory