\textsc{Nasari}: integrating explicit knowledge and corpus statistics for a multilingual representation of concepts and entities

DOI10.1016/j.artint.2016.07.005zbMath1386.68184OpenAlexW2517456239WikidataQ98801376 ScholiaQ98801376MaRDI QIDQ329043

Roberto Navigli, José Camacho-Collados, Mohammad Taher Pilehvar

Publication date: 21 October 2016

Published in: Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.artint.2016.07.005

zbMATH Keywords

lexical semanticsdomain labelingsemantic representationsemantic similaritysense clusteringword sense disambiguation

Mathematics Subject Classification ID

Natural language processing (68T50)

Related Items (5)

LMMS reloaded: transformer-based sense embeddings for disambiguation and beyond ⋮ MultiWiBi: the multilingual Wikipedia bitaxonomy project ⋮ Nasari ⋮ Toward any-language zero-shot topic classification of textual documents ⋮ A cross-lingual sentence pair interaction feature capture model based on pseudo-corpus and multilingual embedding

Uses Software

• WordNet
• word2vec
• DKPro Similarity
• El92
• Simlex-999
• BabelNet
• RoWordNet
• AutoExtend

Cites Work

• BabelNet: the automatic construction, evaluation and application of a wide-coverage multilingual semantic network
• Collaboratively built semi-structured content and artificial intelligence: the story so far
• From senses to texts: an all-in-one graph-based approach for measuring semantic similarity
• Evaluating WordNet-based Measures of Lexical Semantic Relatedness
• A vector space model for automatic indexing
• From Frequency to Meaning: Vector Space Models of Semantics
• Unnamed Item
• Unnamed Item

This page was built for publication: \textsc{Nasari}: integrating explicit knowledge and corpus statistics for a multilingual representation of concepts and entities