Interpretable Word Embedding Contextualization

WS 2018 Kyoung-Rok JangSung-Hyon MyaengSang-Bum Kim

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... (read more)

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