Visualize: Table 1 & 3 & 4.
Description: "We introduce an additive
modification to the objective function of the embedding learning
algorithm that encourages the embedding vectors of words that
are semantically related to a predefined concept to take larger
values along a specified dimension, while leaving the original
semantic learning mechanism mostly unaffected. In other words,
we align words that are already determined to be related, along
predefined concepts. "