Structured term recognition in medical text

In this work we present a novel approach to bootstrap domain specific terminology, namely Structured Term Recognition, and we apply it to the medical domain. In contrast to previous approaches, based on observing distributional properties of terminology with respect to their contexts, our method analyzes the "internal structure" of multi-word terms by learning patterns of word clusters. Evaluation shows that our method can be used to boost the performances of term recognition systems based on dictionary lookup while extending the coverage of large ontologies like UMLS. © 2012 The COLING.