TY - GEN
T1 - Using second-order vectors in a knowledge-based method for acronym disambiguation
AU - Mcinnes, Bridget T.
AU - Pedersen, Ted
AU - Liu, Ying
AU - Pakhomov, Serguei V.
AU - Melton, Genevieve B.
PY - 2011
Y1 - 2011
N2 - 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 distinct representation of the long-form and potentially enhances automated disambiguation.
AB - 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 distinct representation of the long-form and potentially enhances automated disambiguation.
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M3 - Conference contribution
AN - SCOPUS:84857773950
SN - 9781932432923
T3 - CoNLL 2011 - Fifteenth Conference on Computational Natural Language Learning, Proceedings of the Conference
SP - 145
EP - 153
BT - CoNLL 2011 - Fifteenth Conference on Computational Natural Language Learning, Proceedings of the Conference
T2 - 15th Conference on Computational Natural Language Learning, CoNLL 2011
Y2 - 23 June 2011 through 24 June 2011
ER -