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Non-Parametric Word Sense Disambiguation for Historical Languages
NLP4DH, 2022Recent approaches to Word Sense Disambiguation (WSD) have profited from the enhanced contextualized word representations coming from contemporary Large Language Models (LLMs).
Enrique Manjavacas Arevalo +1 more
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WIREs Data Mining Knowl. Discov., 2022
In communication, textual data are a vital attribute. In all languages, ambiguous or polysemous words' meaning changes depending on the context in which they are used.
S. Kaddoura, Rowanda D. Ahmed, J. D.
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In communication, textual data are a vital attribute. In all languages, ambiguous or polysemous words' meaning changes depending on the context in which they are used.
S. Kaddoura, Rowanda D. Ahmed, J. D.
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Word sense disambiguation for Turkish
2009 24th International Symposium on Computer and Information Sciences, 2009Word Sense Disambiguation (WSD) is the core and one of the hardest problems of many Natural Language Processing tasks. WSD is considered as an AI-complete problem. Although there are many approaches trying to solve this problem, many of them are not adequate to solve WSD problem for Turkish.
Mert, Ezgi, Dalkılıç, Gökhan
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Research on Word Sense Disambiguation
Advanced Materials Research, 2011At present, how to make the computer understand the text message of humanity automatically is a very important issue in computer information technology field. And the problem of word sense disambiguation is a bottleneck of the understanding of natural language.
Jing Wen Zhan, Yan Min Chen
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Word Sense Disambiguation for Assamese
2016 IEEE 6th International Conference on Advanced Computing (IACC), 2016Word Sense Disambiguation (WSD) is the process ofidentifying the proper sense of an ambiguous word depending onthe particular context. It is to find the accurate sense si among theset of senses {s1, s2, , sn}. This task was motivated by itsinterpretation in various Natural Language Processing (NLP) applications like IR, MT, QA, TC, SP etc.
Shikhar Kr. Sarma, Jumi Sarmah
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Word Sense Disambiguation [PDF]
, 1988 Computational lexical approaches to disambiguation divide into syntactic category assignment such as whether farm is a noun or a verb (Milne, 1986) and word sense disambiguation within syntactic category.9 The latter problem is the subject of this chapter.
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Corpus and Word Sense Disambiguation
2018Every natural language has a large set of words, which, when these are used in a piece of text, may vary in sense denotation. It has been noted that for ages that context, where these words are found to be used, can play an explicit and active role to influence the words to deviate from the original sense to generate new senses.
Niladri Sekhar Dash, L. Ramamoorthy
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The Effect of Windowing in Word Sense Disambiguation
2005In this paper, the effect of different windowing schemes to the success rate of word sense disambiguation is probed. In these windowing schemes it is considered that the impact of a neighbor word to the correct sense of the target word should be somewhat related to it’s distance to the target word.
Karsligil, Elif +2 more
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Trends in word sense disambiguation
Artificial Intelligence Review, 2012The problem and process of identifying the meaning of a word as per its usage context is called word sense disambiguation (WSD). Although research in this field has been ongoing for the past forty years, a distinct change of techniques adopted can be observed over time.
R. V. Vidhu Bhala, S. Abirami
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Malayalam word sense disambiguation
2010 IEEE International Conference on Computational Intelligence and Computing Research, 2010This paper presents an outline of our work to develop a word sense disambiguation system in Malayalam. Word sense disambiguation (WSD) is a linguistically based mechanism for automatically defining the correct sense of a word in the context. WSD is a long standing problem in computational linguistics.
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