Results 51 to 60 of about 1,917 (147)
Journal of Language ModellingWe develop a three-part approach to Verb Sense Disambiguation (VSD) in German. After considering a set of lexical resources and corpora, we arrive at a statistically motivated selection of a subset of verbs and their senses from GermaNet.
Dominik Mattern +3 more
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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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Toward Universal Word Sense Disambiguation Using Deep Neural Networks
IEEE Access, 2019 Traditionally, approaches based on neural networks to solve the problem of disambiguation of the meaning of words (WSD) use a set of classifiers at the end, which results in a specialization in a single set of words-those for which they were trained ...
Hiram Calvo +3 more
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Contextual word sense tuning and disambiguation
Applied Artificial Intelligence, 1997 The discrimination of word senses, word sense disambiguation (WSD), is a major problem in natural language processing (NLP) applications, e.g., text classification and understanding. The problem of determining the correct sense of lexical items in raw texts is relevant to the activities of categorization, machine translation, information retrieval, and
Roberto Basili 0001 +2 more
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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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WORD SENSE DISAMBIGUATION USING FUZZY SEMANTIC-BASED STRING SIMILARITY MODEL
Malaysian Journal of Computing, 2018 Sentences are the language of human communication. This communication medium is so fluid that words and meaning can have many interpretations by readers.
Amir Abd-Rashid, Shuzlina Abdul-Rahman, Nor Nadiah Yusof, Azlinah Mohamed
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Comparing children and large language models in word sense disambiguation: Insights and challenges
Language Development ResearchUnderstanding how children process ambiguous words is a challenge because sense disambiguation is a complex task that depends on both bottom-up and top-down cues.
Abdellah Fourtassi +2 more
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A Systematic Analysis of Various Word Sense Disambiguation Approaches
Advances in Distributed Computing and Artificial Intelligence JournalThe process of finding the correct sense of a word in context is known as word sense disambiguation (WSD). In the field of natural language processing, WSD has become a growing research area.
Chandra Ganesh +3 more
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