Results 21 to 30 of about 105,540 (133)
WORD SENSE DISAMBIGUATION FOR TAMIL LANGUAGE USING PART-OF-SPEECH AND CLUSTERING TECHNIQUE [PDF]
Journal of Engineering Science and Technology, 2017 Word sense disambiguation is an important task in Natural Language Processing (NLP), and this paper concentrates on the problem of target word selection in machine translation.
P. ISWARYA, V. RADHA
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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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A Quadratic 0-1 Programming Approach for Word Sense Disambiguation [PDF]
arXiv, 2022 Word Sense Disambiguation (WSD) is the task to determine the sense of an ambiguous word in a given context. Previous approaches for WSD have focused on supervised and knowledge-based methods, but inter-sense interactions patterns or regularities for disambiguation remain to be found.
arxiv
Biomedical Word Sense Disambiguation Based on Graph Attention Networks
IEEE Access, 2022 Biomedical words have many semantics. Biomedical word sense disambiguation (WSD) is an important research issue in biomedicine field. Biomedical WSD refers to the process of determining meanings of ambiguous word according to its context.
Chun-Xiang Zhang +2 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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Chinese Word Sense Embedding with SememeWSD and Synonym Set [PDF]
arXiv, 2022 Word embedding is a fundamental natural language processing task which can learn feature of words. However, most word embedding methods assign only one vector to a word, even if polysemous words have multi-senses. To address this limitation, we propose SememeWSD Synonym (SWSDS) model to assign a different vector to every sense of polysemous words with ...
arxiv
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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From Word Alignment to Word Senses, via Multilingual Wordnets [PDF]
Computer Science Journal of Moldova, 2006 Most of the successful commercial applications in language processing (text and/or speech) dispense with any explicit concern on semantics, with the usual motivations stemming from the computational high costs required for dealing with semantics, in case
Dan Tufis
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Word Sense Disambiguation Based on Large Scale Polish CLARIN Heterogeneous Lexical Resources
Cognitive Studies | Études cognitives, 2015 Word Sense Disambiguation Based on Large Scale Polish CLARIN Heterogeneous Lexical Resources Lexical resources can be applied in many different Natural Language Engineering tasks, but the most fundamental task is the recognition of word senses used in ...
Paweł Kędzia +2 more
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Capsule Network Improved Multi-Head Attention for Word Sense Disambiguation
Applied Sciences, 2021 Word sense disambiguation (WSD) is one of the core problems in natural language processing (NLP), which is to map an ambiguous word to its correct meaning in a specific context.
Jinfeng Cheng, Weiqin Tong, Weian Yan
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