Mining a lexicon of technical terms and lay equivalents

Authors:
Noemie Elhadad;Komal Sutaria
Affiliations:
The City College of New York, New York, NY;The City College of New York, New York, NY
Venue:
BioNLP '07 Proceedings of the Workshop on BioNLP 2007: Biological, Translational, and Clinical Language Processing
Year:
2007

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Abstract

We present a corpus-driven method for building a lexicon of semantically equivalent pairs of technical and lay medical terms. Using a parallel corpus of abstracts of clinical studies and corresponding news stories written for a lay audience, we identify terms which are good semantic equivalents of technical terms for a lay audience. Our method relies on measures of association. Results show that, despite the small size of our corpus, a promising number of pairs are identified.