(2003), word embeddings aim at representing, i.e., embedding, the ideal semantic space of words in a real-valued continuous vector space.
to traditional distributional techniques, such as Latent Semantic Analysis (Landauer and Dutnais, 1997, LSA) and Latent Dirichlet Allocation (Blei et al., 2003, LDA), Bengio et al.