Disambiguation of medline abstracts using topic models
Proceedings of the ACM fifth international workshop on Data and text mining in biomedical informatics
Resolving ambiguity in biomedical text to improve summarization
Information Processing and Management: an International Journal
Scaling up WSD with automatically generated examples
BioNLP '12 Proceedings of the 2012 Workshop on Biomedical Natural Language Processing
Semantic relatedness for biomedical word sense disambiguation
TextGraphs-7 '12 Workshop Proceedings of TextGraphs-7 on Graph-based Methods for Natural Language Processing
Biomedical text disambiguation using UMLS
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Evaluating measures of semantic similarity and relatedness to disambiguate terms in biomedical text
Journal of Biomedical Informatics
Determining the difficulty of Word Sense Disambiguation
Journal of Biomedical Informatics
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Motivation: Word Sense Disambiguation (WSD), automatically identifying the meaning of ambiguous words in context, is an important stage of text processing. This article presents a graph-based approach to WSD in the biomedical domain. The method is unsupervised and does not require any labeled training data. It makes use of knowledge from the Unified Medical Language System (UMLS) Metathesaurus which is represented as a graph. A state-of-the-art algorithm, Personalized PageRank, is used to perform WSD. Results: When evaluated on the NLM-WSD dataset, the algorithm outperforms other methods that rely on the UMLS Metathesaurus alone. Availability: The WSD system is open source licensed and available from http://ixa2.si.ehu.es/ukb/. The UMLS, MetaMap program and NLM-WSD corpus are available from the National Library of Medicine http://www.nlm.nih.gov/research/umls/, http://mmtx.nlm.nih.gov and http://wsd.nlm.nih.gov. Software to convert the NLM-WSD corpus into a format that can be used by our WSD system is available from http://www.dcs.shef.ac.uk/~marks/biomedical_wsd under open source license. Contact: m.stevenson@dcs.shef.ac.uk