Deep Learning Model and Its Application in Big Data

  • Yuanming Zhou
  • Shifeng ZhaoEmail author
  • Xuesong Wang
  • Wei Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10918)


In the era of big data, many of the data that previously seemed hard to collect and use began to be utilized, resulting in an increase of millions of the data to be processed. In order to obtain valuable information, large-scale data can be processed and analyzed using a well-developed deep learning framework. This study introduces the concept of deep learning and three common deep learning models - Multilayer Perceptron, Convolutional Neural Network and Recurrent Neural Network, and analyzes the improvement of the model in dealing with large-scale data and gives the capacity and diversity analysis. Introducing the innovative application of deep learning in various fields under big data. Looking forward to the development of deep learning in the era of big data, the integration of big data and in-depth learning will make breakthroughs in various fields. Through constant innovation, they will gradually create more value for mankind.


Big data Deep learning Multilayer Perceptron Convolutional neural network Recurrent neural network 



This work was supported by Beijing Natural Science Foundation (Grant No. 4174094).


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Yuanming Zhou
    • 1
  • Shifeng Zhao
    • 1
    Email author
  • Xuesong Wang
    • 1
  • Wei Liu
    • 2
  1. 1.College of Information Science and TechnologyBeijing Normal UniversityBeijingChina
  2. 2.Department of PsychologyBeijing Normal UniversityBeijingChina

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