A corpus-based approach to language learning
A corpus-based approach to language learning
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
A robust linguistic platform for efficient and domain specific web content analysis
Large Scale Semantic Access to Content (Text, Image, Video, and Sound)
Improving term extraction with terminological resources
FinTAL'06 Proceedings of the 5th international conference on Advances in Natural Language Processing
Developing a robust part-of-speech tagger for biomedical text
PCI'05 Proceedings of the 10th Panhellenic conference on Advances in Informatics
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
BioNLP '12 Proceedings of the 2012 Workshop on Biomedical Natural Language Processing
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Acquisition and enrichment of lexical resources have long been acknowledged as an important research in the area of computational linguistics. Nevertheless, we notice that such resources, particularly in specialised domains, are missing. However, specialised domains, i.e. biomedicine, propose several structured terminologies. In this paper, we propose a high-quality method for exploiting a structured terminology and inferring a specialised elementary synonym lexicon. The method is based on the analysis of syntactic structure of complex terms. We evaluate the approach on the biomedical domain by using the terminological resource Gene Ontology. It provides results with over 93% precision. Comparison with an existing synonym resource (the general-language resource WordNet) shows that there is a very small overlap between the induced lexicon of synonyms and the WordNet synsets.