Results 31 to 40 of about 2,548,691 (245)
Data-driven semantic analysis for multilingual WSD and lexical selection in translation [PDF]
, 2009 A common way of describing the senses of ambiguous words in multilingual Word Sense Disambiguation (WSD) is by reference to their translation equivalents in another language.
Apidianaki, Marianna
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SBU-WSD-Corpus: A Sense Annotated Corpus for Persian All-words Word Sense Disambiguation [PDF]
International Journal of Web Research, 2022 Word Sense Disambiguation (WSD) is a long standing task in Natural Language Processing (NLP) that aims to automatically identify the most relevant meaning of the words in a given context.
Hossein Rouhizadeh +2 more
doaj +1 more source
Using triangulation to identify word senses [PDF]
Word sense disambiguation is the task of determining which sense of a word is intended from its context. Previous methods have found the lack of training data and the restrictiveness of dictionaries' choices of senses to be major stumbling blocks.
Roberts, Paul J. +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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A Method of Word Sense Disambiguation with Restricted Boltzmann Machine
Journal of Harbin University of Science and Technology, 2019 For polysemy phenomenon in Chinese, Restricted Boltzmann Machine (RBM) is adopted to determine the true meaning of ambiguous vocabulary where linguistic knowledge in context is used Word form, part of speech and semantic categories in four left and ...
ZHANG Chun-xiang +2 more
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Hybrid Sense Classification Method for Large-Scale Word Sense Disambiguation
IEEE Access, 2020 Word sense disambiguation (WSD) is a task of determining a reasonable sense of a word in a particular context. Although recent studies have demonstrated some progress in the advancement of neural language models, the scope of research is still such that ...
Yoonseok Heo, Sangwoo Kang, Jungyun Seo
doaj +1 more source
Graph Convolutional Network for Word Sense Disambiguation
Discrete Dynamics in Nature and Society, 2021 Word sense disambiguation (WSD) is an important research topic in natural language processing, which is widely applied to text classification, machine translation, and information retrieval.
Chun-Xiang Zhang +3 more
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Determining the difficulty of Word Sense Disambiguation [PDF]
Journal of Biomedical Informatics, 2014 Automatic processing of biomedical documents is made difficult by the fact that many of the terms they contain are ambiguous. Word Sense Disambiguation (WSD) systems attempt to resolve these ambiguities and identify the correct meaning. However, the published literature on WSD systems for biomedical documents report considerable differences in ...
McInnes, B, Stevenson, R.M
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Complexity, 2020 In natural language, the phenomenon of polysemy is widespread, which makes it very difficult for machines to process natural language. Word sense disambiguation is a key issue in the field of natural language processing.
Lei Wang, Qun Ai
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SensPick: Sense Picking for Word Sense Disambiguation [PDF]
2021 IEEE 15th International Conference on Semantic Computing (ICSC), 2021 Word sense disambiguation (WSD) methods identify the most suitable meaning of a word with respect to the usage of that word in a specific context. Neural network-based WSD approaches rely on a sense-annotated corpus since they do not utilize lexical resources.
S. M. Zobaed +3 more
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