Results 11 to 20 of about 46,318 (263)
WordNet: A Lexical Database for English [PDF]
Communications of the ACM, 1995 Because meaningful sentences are composed of meaningful words, any system that hopes to process natural languages as people do must have information about words and their meanings.
G. Miller
semanticscholar +6 more sources
Proceedings of The Third Workshop on Representation Learning for NLP, 2018 Semantic networks and semantic spaces have been two prominent approaches to represent lexical semantics. While a unified account of the lexical meaning relies on one being able to convert between these representations, in both directions, the conversion ...
Chakaveh Saedi +3 more
semanticscholar +3 more sources
An Efficient Approach for Measuring Semantic Similarity Combining WordNet and Wikipedia
IEEE Access, 2020 The measurement of semantic similarity between concepts is an important research topic in natural language processing. In the past, several approaches for measuring the semantic similarity between concepts have been proposed based on WordNet or Wikipedia.
Fei Li +5 more
doaj +2 more sources
Automatic Construction of Persian ICT WordNet using Princeton WordNet [PDF]
Journal of Artificial Intelligence and Data Mining, 2019 WordNet is a large lexical database of English language, in which, nouns, verbs, adjectives, and adverbs are grouped into sets of cognitive synonyms (synsets). Each synset expresses a distinct concept. Synsets are interlinked by both semantic and lexical
A. Ahmadi Tameh +2 more
doaj +2 more sources
WordNet, EuroWordNet and Global WordNet
Revue française de linguistique appliquée, 2002 On se propose de presenter ici brievement l’architecture de la base de donnees WordNeet, concue pour representer des relations conceptuelles et construite initialement pour l’anglais, ainsi que les prolongements qui en ont ete faits sous le nom de EuroWordNet pour sept autres langues europeennes.
Piek Vossen
openalex +5 more sources
Evaluating WordNet-based Measures of Lexical Semantic Relatedness [PDF]
International Conference on Computational Logic, 2006 The quantification of lexical semantic relatedness has many applications in NLP, and many different measures have been proposed. We evaluate five of these measures, all of which use WordNet as their central resource, by comparing their performance in ...
Alexander Budanitsky, Graeme Hirst
openalex +2 more sources
The Arabic ontology – an Arabic wordnet with ontologically clean content [PDF]
Appl. Ontology, 2020 We present a formal Arabic wordnet built on the basis of a carefully designed ontology hereby referred to as the Arabic Ontology. The ontology provides a formal representation of the concepts that the Arabic terms convey, and its content was built with ...
Mustafa Jarrar
semanticscholar +1 more source
Synonym‐based multi‐keyword ranked search with secure k‐NN in 6G network
IET Networks, EarlyView., 2022 Abstract Sixth Generation (6G) integrates the next generation communication systems such as maritime, terrestrial, and aerial to offer robust network and massive device connectivity with ultra‐low latency requirement. The cutting edge technologies such as artificial intelligence, quantum machine learning, and millimetre enable hyper‐connectivity to ...
Deebak Bakkiam David, Fadi Al‐Turjman
wiley +1 more source
Language Modelling Makes Sense: Propagating Representations through WordNet for Full-Coverage Word Sense Disambiguation [PDF]
Annual Meeting of the Association for Computational Linguistics, 2019 Contextual embeddings represent a new generation of semantic representations learned from Neural Language Modelling (NLM) that addresses the issue of meaning conflation hampering traditional word embeddings.
Daniel Loureiro, A. Jorge
semanticscholar +1 more source
Aproximación al trasvase automático de predicados de FrameNet al español mediante WordNet
Revista de Lingüística y Lenguas Aplicadas, 2021 Dentro del procesamiento del lenguaje, los recursos lingüísticos son descripciones estructuradas y detalladas de una determinada lengua, esenciales a la hora de estudiar el lenguaje y crear aplicaciones.
Mario Crespo Miguel
doaj +1 more source