Results 71 to 80 of about 83,244 (255)
Subjectivity word sense disambiguation [PDF]
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing Volume 1 - EMNLP '09, 2009 This paper investigates a new task, subjectivity word sense disambiguation (SWSD), which is to automatically determine which word instances in a corpus are being used with subjective senses, and which are being used with objective senses. We provide empirical evidence that SWSD is more feasible than full word sense disambiguation, and that it can be ...
Janyce Wiebe, Rada Mihalcea, Cem Akkaya
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Learning to Learn to Disambiguate: Meta-Learning for Few-Shot Word Sense Disambiguation [PDF]
Findings, 2020 The success of deep learning methods hinges on the availability of large training datasets annotated for the task of interest. In contrast to human intelligence, these methods lack versatility and struggle to learn and adapt quickly to new tasks, where ...
Nithin Holla +3 more
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Incorporating Glosses into Neural Word Sense Disambiguation [PDF]
Annual Meeting of the Association for Computational Linguistics, 2018 Word Sense Disambiguation (WSD) aims to identify the correct meaning of polysemous words in the particular context. Lexical resources like WordNet which are proved to be of great help for WSD in the knowledge-based methods.
Fuli Luo +4 more
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Chinese Word Sense Disambiguation using a LSTM
ITM Web of Conferences, 2017 Word sense disambiguation (WSD) is a challenging natural language processing (NLP) problem. We propose a new strategy for WSD, which at first replaces the interesting word in a sentence by the different synonyms corresponding to the different meanings ...
Sun Xue-Ren +3 more
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Word vs. Class-Based Word Sense Disambiguation [PDF]
, 2015 As empirically demonstrated by the Word Sense Disambiguation (WSD) tasks of the last SensEval/SemEval exercises, assigning the appropriate meaning to words in context has resisted all attempts to be successfully addressed.
Izquierdo Beviá, Rubén +2 more
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Word Sense Disambiguation Methods and Algorithms
International Journal of Engineering and Advanced Technology, 2020 This paper discuss various technique of word sense disambiguation. In WSD we disambiguate the correct sense of target word present in the text. WSD is a challenging field in the natural language processing, it helps in information retrieval, information extraction, machine learning.
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Word Sense Disambiguation: A Unified Evaluation Framework and Empirical Comparison
Conference of the European Chapter of the Association for Computational Linguistics, 2017 Word Sense Disambiguation is a long-standing task in Natural Language Processing, lying at the core of human language understanding. However, the evaluation of automatic systems has been problematic, mainly due to the lack of a reliable evaluation ...
Roberto Navigli +2 more
semanticscholar +1 more source
Evaluation of Linguistic Features for Word Sense Disambiguation with Self-Organized Document Maps [PDF]
, 2004 Word sense disambiguation automatically determines the appropriate senses of a word in context. We have previously shown that self-organized document maps have properties similar to a large-scale semantic structure that is useful for word sense ...
Linden, Krister
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A review of word-sense disambiguation methods and algorithms: Introduction
Transactions of the Karelian Research Centre of the Russian Academy of Sciences, 2015 The word-sense disambiguation task is a classification task, where the goal is to predict the meaning of words and phrases with the help of surrounding text.
Tatiana Kaushinis +14 more
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Word Sense Disambiguation: An Overview [PDF]
Language and Linguistics Compass, 2009 AbstractWord sense disambiguation is a subfield of computational linguistics in which computer systems are designed to determine the appropriate meaning of a word as it appears in the linguistic context. This article provides a survey of what has been done in this area: the ways that word meaning can be represented in the computer, the approaches taken
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