Concept information
Preferred term
word embedding
Definition
- "Word embeddings are low-dimensional numeric representations of words generated by artificial intelligence (AI) methods that capture word co-occurrence statistics. The assumption in these models is that words located in close proximity to one another in the vector space are semantically similar. The similarity between two word meanings, such as “plate" and “bowl", can be quantified by taking the cosine distance between the corresponding vectors in the model." (Calistan & Lewis, 2020, p. 3).
Broader concept
Belongs to group
Bibliographic citation(s)
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• Caliskan, A., & Lewis, M. (2020). Social biases in word embeddings and their relation to human cognition. PsyArXiv. https://doi.org/10.31234/osf.io/d84kg
• Document type: empirical study
• Access: open
- • Kumar, A. A. (2021). Semantic memory : A review of methods, models, and current challenges. Psychonomic Bulletin & Review, 28(1), 40‑80. https://doi.org/10.3758/s13423-020-01792-x
• Document type: literature review
• Access: open
- • Lake, B. M., & Murphy, G. L. (2023). Word meaning in minds and machines. Psychological Review, 130(2), 401–431. https://doi.org/10.1037/rev0000297
• Document type: literature review
• Access: closed
Creator
- Frank Arnould
Model of
In other languages
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French
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plongement de mots
URI
http://data.loterre.fr/ark:/67375/P66-M75L9P53-N - • Kumar, A. A. (2021). Semantic memory : A review of methods, models, and current challenges. Psychonomic Bulletin & Review, 28(1), 40‑80. https://doi.org/10.3758/s13423-020-01792-x
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