Efficient Estimation of Word Representations (word2vec)PDF Download

Mikolov and colleagues describe efficient ways to learn vector representations of words from large text collections. The paper connects training objectives with representations that encode useful linguistic relationships.

The familiar analogy examples are a starting point, not the whole result. Look at how the training setup affects what a vector can represent and what context it loses.