Multi-sense embeddings through a word sense disambiguation process

2019/06/14 by Terry Ruas, William I. Grosky, William Grosky +1 · 1 citation
Computer Science · #Advanced Text Analysis Techniques #Annotation #Artificial intelligence #Computer science #Context (archaeology) #Linguistics #Natural Language Processing Techniques #Natural language #Natural language processing #Natural language understanding #Polysemy #Representation (politics) #SemEval #Semantic similarity #Similarity (geometry) #Task (project management) #Topic Modeling #Word (group theory)

paper · doi:10.1016/j.eswa.2019.06.026

openalex publication_date 2019/06/14 · crossref created 2019/06/14 · crossref issued 2019/12/01 · crossref published 2019/12/01 · crossref published-print 2019/12/01 · openalex created_date 2025/10/10 · crossref deposited 2025/10/17 · crossref indexed 2026/06/13 · openalex updated_date 2026/08/05

Citations

• Efficient Estimation of Word Representations in Vector Space
• SimLex-999: Evaluating Semantic Models With (Genuine) Similarity Estimation
• BabelNet: The automatic construction, evaluation and application of a wide-coverage multilingual semantic network
• Distributed Representations of Words and Phrases and their Compositionality
• A vector space model for automatic indexing
• A note on two problems in connexion with graphs
• sense2vec - A Fast and Accurate Method for Word Sense Disambiguation In Neural Word Embeddings
• Enriching Word Vectors with Subword Information
• AutoExtend: Combining Word Embeddings with Semantic Resources
• Universal Sentence Encoder
• Distributional Structure

Cited by

• Word-sense disambiguation [wikipedia]