Application of output side weights on Word2Vec

Abstract

A word vector of distributed representation that embeds the semantic relation among words into the vector using Word2Vec has attracted attention in recent years. Furthermore, this word vector has become widely used in the field of Natural Language Processing such as parsing and document classification, and its effectiveness has reported. Generally, only the input side weights on Word2Vec are used as the elements of a word vector, and the output side weights generated at the same time are not used. On the other hand, the authors focus on the usefulness of the paired output side weights with the input side ones. In this paper, we propose a word vector using the input and output side weights together. In addition, we experimentally investigate the performance of the proposed word vector.