Interpretable Word Embedding Contextualization
Kyoung-Rok Jang, Sung-Hyon Myaeng, Sang‐Bum Kim · 2018
In this paper, we propose a method of calibrating a word embedding, so that the semantic it conveys becomes more relevant to the context.Our method is novel because the output shows clearly which senses that were originally presented in a target word embedding become stronger or weaker.This is possible by utilizing the technique of using sparse coding to recover senses that comprises a word embedding.