Results 41 to 50 of about 83,408 (318)

Comparative Analysis of Recurrent Neural Network Architectures for Arabic Word Sense Disambiguation

open access: yesInternational Conference on Web Information Systems and Technologies, 2022
: Word Sense Disambiguation (WSD) refers to the process of discovering the correct sense of an ambiguous word occurring in a given context. In this paper, we address the problem of Word Sense Disambiguation of low-resource languages such as Arabic ...
R. Saidi, Fethi Jarray, M. Alsuhaibani
semanticscholar   +1 more source

DiBiMT: A Novel Benchmark for Measuring Word Sense Disambiguation Biases in Machine Translation

open access: yesAnnual Meeting of the Association for Computational Linguistics, 2022
Lexical ambiguity poses one of the greatest challenges in the field of Machine Translation. Over the last few decades, multiple efforts have been undertaken to investigate incorrect translations caused by the polysemous nature of words.
Niccolò Campolungo   +3 more
semanticscholar   +1 more source

Framing Word Sense Disambiguation as a Multi-Label Problem for Model-Agnostic Knowledge Integration

open access: yesConference of the European Chapter of the Association for Computational Linguistics, 2021
Recent studies treat Word Sense Disambiguation (WSD) as a single-label classification problem in which one is asked to choose only the best-fitting sense for a target word, given its context.
Simone Conia, Roberto Navigli
semanticscholar   +1 more source

Graph Convolutional Network for Word Sense Disambiguation

open access: yesDiscrete 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
doaj   +1 more source

Unsupervised Word Sense Disambiguation Rivaling Supervised Methods

open access: yesAnnual Meeting of the Association for Computational Linguistics, 1995
This paper presents an unsupervised learning algorithm for sense disambiguation that, when trained on unannotated English text, rivals the performance of supervised techniques that require time-consuming hand annotations.
David Yarowsky
semanticscholar   +1 more source

The Socialocene: From Capitalocene to Transnational Waste Regimes

open access: yesAntipode, EarlyView., 2022
Abstract In this article I will present a relational, and multiscalar, perspective on how state socialism interacted with and shaped the Capitalocene. I introduce a heuristic device, the term Socialocene, a transnational waste regime dominant through the Cold War‐era, that is, during what Will Steffen and colleagues call “the great acceleration”.
Zsuzsa Gille
wiley   +1 more source

Hybrid Sense Classification Method for Large-Scale Word Sense Disambiguation

open access: yesIEEE 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

Word sense disambiguation in queries [PDF]

open access: yesProceedings of the 14th ACM international conference on Information and knowledge management, 2005
This paper presents a new approach to determine the senses of words in queries by using WordNet. In our approach, noun phrases in a query are determined first. For each word in the query, information associated with it, including its synonyms, hyponyms, hypernyms, definitions of its synonyms and hyponyms, and its domains, can be used for word sense ...
Shuang Liu, Clement Yu, Weiyi Meng
openaire   +2 more sources

Breaking Through the 80% Glass Ceiling: Raising the State of the Art in Word Sense Disambiguation by Incorporating Knowledge Graph Information

open access: yesAnnual Meeting of the Association for Computational Linguistics, 2020
Neural architectures are the current state of the art in Word Sense Disambiguation (WSD). However, they make limited use of the vast amount of relational information encoded in Lexical Knowledge Bases (LKB).
Michele Bevilacqua, Roberto Navigli
semanticscholar   +1 more source

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