Digital Scholarship Labs

Word2vec is a high-dimensional word-embedding unsupervised learning algorithm. The most defining characteristics of word2vec is that word that appear in similar context will be close together in the vector-space.
Furthermore distance between words can be generalized and produce qualified guesses for analogies as: man is to woman as king is to ? (queen).
These two methods can be explored here on various corpora. You can request a new corpus: Mail KBLabs
About the corpora:
is to as is to ?
Calculating. Might take up to 1 minute for larger corpora like Gutenberg and Newspapers