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... > information entity > theoretical entity > model > computational model > distributional model > word embedding

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).

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Bibliographic citation(s)

  • • 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

    [Study 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

    [Study 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

    [Study type: literature review / Access: closed]

Creator

  • Frank Arnould

Model of

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URI

http://data.loterre.fr/ark:/67375/P66-M75L9P53-N

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