Application of deep learning in natural language processing (Version 0.76) _ Depth Learning

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Author: Zhang Junlin

Timestamp:2014-10-3

This paper mainly summarizes the application methods and techniques of deep learning in natural language processing in the last two years, and the relevant PPT content please refer to this link, which lists the main outlines. Brief introduction to outline and depth of study • Basic questions: Language representation problem –word embedding– representation of different granularity language units • Characters/word/words/phrases/sentences/documents • The depth of the focus Learning Model –rae (recursive autoencoders)/tensor network/convolution Network • Application of depth learning in natural language processing – deep learning for language models-deep learning for Chinese participle-deep learning For knowledge mining – deep learning for emotional computing – deep learning for machine translation-depth learning for IR exploration and thinking on paraphrase– depth learning