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Deep Learning and Vector Space Model

  • Grigori Sidorov
Chapter
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

In recent years, a novel paradigm appeared related to application of neural networks to any tasks related to artificial intelligence [59], in particular, in natural language processing [39]. It became extremely popular in NLP area after works of Mikolov et al. starting in 2013 [74, 75]. The main idea of this paradigm is to apply neural networks for automatic learning of relevant features with various levels of generalization in vector space model. Sometimes this model of representation of objects is called continuous vector space model. In general, this paradigm is called “deep learning.”

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Copyright information

© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Grigori Sidorov
    • 1
  1. 1.Instituto Politécnico NacionalCentro de Investigación en ComputaciónMexico CityMexico

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