Semantic relatedness for biomedical word sense disambiguation

Authors:
Kiem-Hieu Nguyen;Cheol-Young Ock
Affiliations:
University of Ulsan, Ulsan, Korea;University of Ulsan, Ulsan, Korea
Venue:
TextGraphs-7 '12 Workshop Proceedings of TextGraphs-7 on Graph-based Methods for Natural Language Processing
Year:
2012

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Abstract

This paper presents a graph-based method for all-word word sense disambiguation of biomedical texts using semantic relatedness as edge weight. Semantic relatedness is derived from a term-topic co-occurrence matrix. The sense inventory is generated by the MetaMap program. Word sense disambiguation is performed on a disambiguation graph via a vertex centrality measure. The proposed method achieves competitive performance on a benchmark dataset.