Disambiguating ambiguous biomedical terms in biomedical narrative text: an unsupervised method
Computers and Biomedical Research
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
A decision tree of bigrams is an accurate predictor of word sense
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Exploiting parallel texts for word sense disambiguation: an empirical study
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
SaRAD: a Simple and Robust Abbreviation Dictionary
Bioinformatics
Resolving abbreviations to their senses in Medline
Bioinformatics
Medstract: creating large-scale information servers for biomedical libraries
BioMed '02 Proceedings of the ACL-02 workshop on Natural language processing in the biomedical domain - Volume 3
A large scale, corpus-based approach for automatically disambiguating biomedical abbreviations
ACM Transactions on Information Systems (TOIS)
ADAM: another database of abbreviations in MEDLINE
Bioinformatics
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Gene symbol disambiguation using knowledge-based profiles
Bioinformatics
Inter-coder agreement for computational linguistics
Computational Linguistics
A discriminative alignment model for abbreviation recognition
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Disambiguation of ambiguous biomedical terms using examples generated from the UMLS Metathesaurus
Journal of Biomedical Informatics
Data-driven computational linguistics at FaMAF-UNC, Argentina
YIWCALA '10 Proceedings of the NAACL HLT 2010 Young Investigators Workshop on Computational Approaches to Languages of the Americas
ICE-TEA: in-context expansion and translation of English abbreviations
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part II
Using second-order vectors in a knowledge-based method for acronym disambiguation
CoNLL '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning
Artificial Intelligence in Medicine
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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Abbreviations are common in biomedical documents and many are ambiguous in the sense that they have several potential expansions. Identifying the correct expansion is necessary for language understanding and important for applications such as document retrieval. Identifying the correct expansion can be viewed as a Word Sense Disambiguation (WSD) problem. A WSD system that uses a variety of knowledge sources, including two types of information specific to the biomedical domain, is also described. This system was tested on a corpus of ambiguous abbreviations, created by automatically identifying the correct expansion in Medline abstracts, and found to identify the correct expansion with up to 99% accuracy.