Using Second-order Vectors in a Knowledge-based Method for Acronym Disambiguation

Abstract

In this paper, we introduce a knowledge-based method to disambiguate biomedical acronyms using second-order co-occurrence vectors. We create these vectors using information about a long-form obtained from the Unified Medical Language System and Medline. We evaluate this method on a dataset of 18 acronyms found in biomedical text. Our method achieves an overall accuracy of 89%. The results show that using second-order features provide a dis-tinct representation of the long-form and po-tentially enhances automated disambiguation. 1