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The Interaction of Knowledge Sources in Word Sense Disambiguation [PDF]
Computational Linguistics, 2021 Word sense disambiguation (WSD) is a computational linguistics task likely to benefit from the tradition of combining different knowledge sources in artificial in telligence research.
Mark Stevenson, Yorick Wilks
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Role of Genetic Algorithm in Optimization of Hindi Word Sense Disambiguation
IEEE Access, 2022 The Word Sense Disambiguation system is widely used in many fields, including business, research, education, and government organizations. The availability of natural language data on the internet has grown in tandem with the rapid advancement of ...
Surbhi Bhatia +2 more
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Word Sense Disambiguation: A Survey
International Journal of Control Theory and Computer Modeling, 2015 In this paper, we made a survey on Word Sense Disambiguation (WSD). Near about in all major languages around the world, research in WSD has been conducted upto different extents. In this paper, we have gone through a survey regarding the different approaches adopted in different research works, the State of the Art in the performance in this domain ...
Alok Ranjan Pal, Diganta Saha
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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. Recent breakthroughs in representation learning have fueled intensive WSD research, resulting in considerable performance improvements, breaching the 80% glass ceiling set by the inter ...
Bevilacqua, Michele +3 more
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Nibbling at the Hard Core of Word Sense Disambiguation
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022 With state-of-the-art systems having finally attained estimated human performance, Word Sense Disambiguation (WSD) has now joined the array of Natural Language Processing tasks that have seemingly been solved, thanks to the vast amounts of knowledge encoded into Transformer-based pre-trained language models. And yet, if we look below the surface of raw
Maru, Marco +3 more
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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
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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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Embeddings for Word Sense Disambiguation: An Evaluation Study [PDF]
Annual Meeting of the Association for Computational Linguistics, 2016 Recent years have seen a dramatic growth in the popularity of word embeddings mainly owing to their ability to capture semantic information from massive amounts of textual content. As a result, many tasks in Natural Language Processing have tried to take
Ignacio Iacobacci +2 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 domain disambiguation via word sense disambiguation [PDF]
Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers on XX - NAACL '06, 2006 Word subject domains have been widely used to improve the performance of word sense disambiguation algorithms. However, comparatively little effort has been devoted so far to the disambiguation of word subject domains. The few existing approaches have focused on the development of algorithms specific to word domain disambiguation.
Antonio Sanfilippo +2 more
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