Distributional Word Embedding Modeling System

A Distributional Word Embedding Modeling System is a dense continuous word modeling system that is a distributional word vector space modeling system which implements a distributional continuous dense word model training algorithm to solve a distributional word embedding modeling task (to produce a distributional dense continuous word vectors based on a distributional model).

• Context:
  • It can range from being a Heuristic Distributional Continuous Dense Word Modeling System to being a Data-Driven Distributional Continuous Dense Word Modeling System.
  • It can produce a Continuous Dense Distributional Word Model.
  • …
• Example(s):
  • word2vec System.
  • …
• Counter-Example(s):
  • Discrete Dense Distributional Word Model Training System.
  • Continuous Sparse Distributional Word Model Training System.
  • Continuous Dense Heuristic Word Model Training System.
• See: Word Model Training System, Dense Word Model Training System, Continuous Word Model Training System.

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References

2013

• (Mikolov et al., 2014) ⇒ Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. (2014). “Distributed Representations of Words and Phrases and their Compositionality.” In: Advances in Neural Information Processing Systems 26 (NIPS 2013).

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