Results 51 to 60 of about 105,540 (133)
An Optimized Lesk-Based Algorithm for Word Sense Disambiguation
Open Computer Science, 2016 Computational complexity is a characteristic of almost all Lesk-based algorithms for word sense disambiguation (WSD). In this paper, we address this issue by developing a simple and optimized variant of the algorithm using topic composition in documents ...
Ayetiran Eniafe Festus, Agbele Kehinde
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Learning Word Sense Embeddings from Word Sense Definitions [PDF]
arXiv, 2016 Word embeddings play a significant role in many modern NLP systems. Since learning one representation per word is problematic for polysemous words and homonymous words, researchers propose to use one embedding per word sense. Their approaches mainly train word sense embeddings on a corpus.
arxiv
Word embeddings and recurrent neural networks based on Long-Short Term Memory nodes in supervised biomedical word sense disambiguation [PDF]
arXiv, 2016 Word sense disambiguation helps identifying the proper sense of ambiguous words in text. With large terminologies such as the UMLS Metathesaurus ambiguities appear and highly effective disambiguation methods are required. Supervised learning algorithm methods are used as one of the approaches to perform disambiguation.
arxiv
A chain dictionary method for Word Sense Disambiguation and applications [PDF]
Studia Universitatis Babes-Bolyai, Special Issue, KEPT 2007,
Knowledge Engineering: Principles and Technologies, Cluj-Napoca, June 6-8,
2007, pp 33-40,, 2008 A large class of unsupervised algorithms for Word Sense Disambiguation (WSD) is that of dictionary-based methods. Various algorithms have as the root Lesk's algorithm, which exploits the sense definitions in the dictionary directly. Our approach uses the lexical base WordNet for a new algorithm originated in Lesk's, namely "chain algorithm for ...
arxiv
PENENTUAN MAKNA KATA DARI FRASE DALAM KALIMAT BAHASA INGGRIS
Rekayasa, 2011 Tokenisasi merupakan proses memecah kalimat menjadi kata, frase atau bentuk lain yang memiliki arti, hasil tokenisasi disebut sebagai token. Tokenisasi adalah langkah prapemrosesan Word Sense Disambiguation (WSD), proses penentuan makna suatu kata ...
Jeany Harmoejanto
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Word sense disambiguation criteria: a systematic study [PDF]
20th International Conference on Computational Linguistics
(COLING-2004) (2004) pp. 910-916, 2005 This article describes the results of a systematic in-depth study of the criteria used for word sense disambiguation. Our study is based on 60 target words: 20 nouns, 20 adjectives and 20 verbs. Our results are not always in line with some practices in the field.
arxiv
Unsupervised Word Sense Disambiguation Using Transformer’s Attention Mechanism
Machine Learning and Knowledge ExtractionTransformer models produce advanced text representations that have been used to break through the hard challenge of natural language understanding. Using the Transformer’s attention mechanism, which acts as a language learning memory, trained on tens of ...
Radu Ion +6 more
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Neural Network Models for Word Sense Disambiguation: An Overview
Cybernetics and Information Technologies, 2018 The following article presents an overview of the use of artificial neural networks for the task of Word Sense Disambiguation (WSD). More specifically, it surveys the advances in neural language models in recent years that have resulted in methods for ...
Popov Alexander
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Using BERT for Word Sense Disambiguation [PDF]
arXiv, 2019 Word Sense Disambiguation (WSD), which aims to identify the correct sense of a given polyseme, is a long-standing problem in NLP. In this paper, we propose to use BERT to extract better polyseme representations for WSD and explore several ways of combining BERT and the classifier.
arxiv
Disambiguierung deutschsprachiger Diskursmarker: Eine Pilot-Studie
Linguistik Online, 2004 Discourse markers such as German aber, wohl or obwohl can be regarded as valuable information for a wide range of text-linguistic applications, since they provide important cues for the interpretation of texts or text segments.
Petra Saskia Bayerl
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