TY - JOUR
T1 - Knowledge-based method for determining the meaning of ambiguous biomedical terms using information content measures of similarity.
AU - McInnes, Bridget T.
AU - Pedersen, Ted
AU - Liu, Ying
AU - Melton, Genevieve B.
AU - Pakhomov, Serguei V.
PY - 2011
Y1 - 2011
N2 - In this paper, we introduce a novel knowledge-based word sense disambiguation method that determines the sense of an ambiguous word in biomedical text using semantic similarity or relatedness measures. These measures quantify the degree of similarity between concepts in the Unified Medical Language System (UMLS). The objective of this work was to develop a method that can disambiguate terms in biomedical text by exploiting similarity information extracted from the UMLS and to evaluate the efficacy of information content-based semantic similarity measures, which augment path-based information with probabilities derived from biomedical corpora. We show that information content-based measures obtain a higher disambiguation accuracy than path-based measures because they weight the path based on where it exists in the taxonomy coupled with the probability of the concepts occurring in a corpus of text.
AB - In this paper, we introduce a novel knowledge-based word sense disambiguation method that determines the sense of an ambiguous word in biomedical text using semantic similarity or relatedness measures. These measures quantify the degree of similarity between concepts in the Unified Medical Language System (UMLS). The objective of this work was to develop a method that can disambiguate terms in biomedical text by exploiting similarity information extracted from the UMLS and to evaluate the efficacy of information content-based semantic similarity measures, which augment path-based information with probabilities derived from biomedical corpora. We show that information content-based measures obtain a higher disambiguation accuracy than path-based measures because they weight the path based on where it exists in the taxonomy coupled with the probability of the concepts occurring in a corpus of text.
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M3 - Article
C2 - 22195148
AN - SCOPUS:84871816935
SN - 1559-4076
VL - 2011
SP - 895
EP - 904
JO - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
JF - AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
ER -