The recognition of the utility of corpus-derived distributed representations of words for a broad range of Natural Language Processing (NLP) tasks (Collobert et al., 2011) has led to a resurgence of interest in methods of distributional semantics.
the neural-probabilistic word representations produced by the Skip-gram and Continuous Bag-of-Words (CBOW) architectures (Mikolov et al., 2013a) implemented in the word2vec and fastText software packages have been extensively evaluated in recent years.