Paper

A Neural Language Model for Dynamically Representing the Meanings of Unknown Words and Entities in a Discourse

This study addresses the problem of identifying the meaning of unknown words or entities in a discourse with respect to the word embedding approaches used in neural language models. We proposed a method for on-the-fly construction and exploitation of word embeddings in both the input and output layers of a neural model by tracking contexts... (read more)

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