Results 11 to 20 of about 83,408 (318)
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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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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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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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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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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A comprehensive dataset for Arabic word sense disambiguation [PDF]
Data in BriefThis data paper introduces a comprehensive dataset tailored for word sense disambiguation tasks, explicitly focusing on a hundred polysemous words frequently employed in Modern Standard Arabic.
Sanaa Kaddoura, Reem Nassar
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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
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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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Word sense disambiguation criteria: a systematic study [PDF]
Proceedings of the 20th international conference on Computational Linguistics - COLING '04, 2004 This article describes the results of a systematic in-depth study of the criteria used for word sense disambiguation. Our study is based on 60 target words: 20 nouns, 20 adjectives and 20 verbs.
Audibert, Laurent
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