Augmenting Semantic Lexicons Using Word Embeddings and Transfer Learning

Augmenting Semantic Lexicons Using Word Embeddings and Transfer Learning

Sentiment-aware intelligent systems are essential to a wide array of applications. These systems are driven by language models which broadly fall into two paradigms: Lexicon-based and contextual. Although recent contextual models are increasingly dominant, we still see demand for lexicon-based model...

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Bibliographic Details
Main Authors: Thayer Alshaabi, Colin M. Van Oort, Mikaela Irene Fudolig, Michael V. Arnold, Christopher M. Danforth, Peter Sheridan Dodds
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-01-01
Series:Frontiers in Artificial Intelligence
Subjects:
sentiment analysis
semantic lexicons
transformers
BERT
FastText
word embedding
Online Access:https://www.frontiersin.org/articles/10.3389/frai.2021.783778/full

Internet

https://www.frontiersin.org/articles/10.3389/frai.2021.783778/full

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