From the linked paper: Many different types of models were proposed for estimating continuous representations of words, including the well-known Latent Semanti

From the linked paper: Many different types of models were proposed for estimating continuous representations of words, including the well-known Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA). In this paper, we focus on distributed representations of words learned by neural networks, as it was previously shown that they perform significantly better than LSA for preserving linear regularities among words