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Deep Learning Methods in Natural Language Processing

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Applied Technologies (ICAT 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1194))

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The purpose of this paper is to make a concise description of the current deep learning methods for natural language processing (NLP) and discusses their advantages and disadvantages. The research further discusses the applicability of each deep learning method in the context of natural language processing. Additionally, a series of significant advances that have driven the processing, understanding, and generation of natural language are also discussed.

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Correspondence to Alexis Stalin Alulema Flores .

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Alulema Flores, A.S. (2020). Deep Learning Methods in Natural Language Processing. In: Botto-Tobar, M., Zambrano Vizuete, M., Torres-Carrión, P., Montes León, S., Pizarro Vásquez, G., Durakovic, B. (eds) Applied Technologies. ICAT 2019. Communications in Computer and Information Science, vol 1194. Springer, Cham.

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-42519-7

  • Online ISBN: 978-3-030-42520-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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