Terminology extraction is an essential step in several fields of natural language processing such as dictionary and ontology extraction. In this paper, we present a novel graph-based approach to terminology extraction. We use SIGNUM, a general purpose graph-based algorithm for binary clustering on directed weighted graphs generated using a metric for multi-word extraction. Our approach is totally knowledge-free and can thus be used on corpora written in any language. Furthermore it is unsupervised, making it suitable for use by non-experts. Our approach is evaluated on the TREC-9 corpus for filtering against the MESH and the UMLS vocabularies.
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