Recent Trends in Word Sense Disambiguation: A Survey [PDF]
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021 Word Sense Disambiguation (WSD) aims at making explicit the semantics of a word in context by identifying the most suitable meaning from a predefined sense inventory.
Michele Bevilacqua +3 more
semanticscholar +5 more sources
Analysis and Evaluation of Language Models for Word Sense Disambiguation
Computational Linguistics, 2021 Transformer-based language models have taken many fields in NLP by storm. BERT and its derivatives dominate most of the existing evaluation benchmarks, including those for Word Sense Disambiguation (WSD), thanks to their ability in capturing context ...
Daniel Loureiro +3 more
doaj +2 more sources
Word Sense Disambiguation by Web Mining for Word Co-occurrence Probabilities [PDF]
, 2004 This paper describes the National Research Council (NRC) Word Sense Disambiguation (WSD) system, as applied to the English Lexical Sample (ELS) task in Senseval-3.
Peter D. Turney
openalex +6 more sources
A Learning-Based Approach for Biomedical Word Sense Disambiguation [PDF]
The Scientific World Journal, 2012 In the biomedical domain, word sense ambiguity is a widely spread problem with bioinformatics research effort devoted to it being not commensurate and allowing for more development.
Hisham Al-Mubaid, Sandeep Gungu
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A Novel Approach to Word Sense Disambiguation Based on Topical and Semantic Association [PDF]
The Scientific World Journal, 2013 Word sense disambiguation (WSD) is a fundamental problem in nature language processing, the objective of which is to identify the most proper sense for an ambiguous word in a given context. Although WSD has been researched over the years, the performance
Xin Wang, Wanli Zuo, Ying Wang
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Word sense disambiguation of acronyms in clinical narratives [PDF]
Frontiers in Digital HealthClinical narratives commonly use acronyms without explicitly defining their long forms. This makes it difficult to automatically interpret their sense as acronyms tend to be highly ambiguous.
Daphné Chopard +2 more
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Supervised Learning and Knowledge-Based Approaches Applied to Biomedical Word Sense Disambiguation [PDF]
Journal of Integrative Bioinformatics, 2017 Word sense disambiguation (WSD) is an important step in biomedical text mining, which is responsible for assigning an unequivocal concept to an ambiguous term, improving the accuracy of biomedical information extraction systems.
Antunes Rui, Matos Sérgio
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TWE‐WSD: An effective topical word embedding based word sense disambiguation
CAAI Transactions on Intelligence Technology, 2021 Word embedding has been widely used in word sense disambiguation (WSD) and many other tasks in recent years for it can well represent the semantics of words.
Lianyin Jia +5 more
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Knowledge-based biomedical word sense disambiguation: comparison of approaches [PDF]
BMC Bioinformatics, 2010 Background Word sense disambiguation (WSD) algorithms attempt to select the proper sense of ambiguous terms in text. Resources like the UMLS provide a reference thesaurus to be used to annotate the biomedical literature.
Aronson Alan R, Jimeno-Yepes Antonio J
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Word sense disambiguation for event trigger word detection in biomedicine [PDF]
BMC Bioinformatics, 2011 This paper describes a method for detecting event trigger words in biomedical text based on a word sense disambiguation (WSD) approach. We first investigate the applicability of existing WSD techniques to trigger word disambiguation in the BioNLP 2009 ...
Martinez David, Baldwin Timothy
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