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Efficiently Processing Big Data in Real-Time Employing Deep Learning Algorithms
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Author(s): Murad Khan (Sarhad University of Science and Information Technology, Pakistan), Bhagya Nathali Silva (Kyungpook National University, South Korea)and Kijun Han (Kyungpook National University, South Korea)
Copyright: 2018
Pages: 18
Source title:
Deep Learning Innovations and Their Convergence With Big Data
Source Author(s)/Editor(s): S. Karthik (SNS College of Technology, Anna University, India), Anand Paul (Kyungpook National University, South Korea)and N. Karthikeyan (Mizan-Tepi University, Ethiopia)
DOI: 10.4018/978-1-5225-3015-2.ch004
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Abstract
Big Data and deep computation are among the buzzwords in the present sophisticated digital world. Big Data has emerged with the expeditious growth of digital data. This chapter addresses the problem of employing deep learning algorithms in Big Data analytics. Unlike the traditional algorithms, this chapter comes up with various solutions to employ advanced deep learning mechanisms with less complexity and finally present a generic solution. The deep learning algorithms require less time to process the big amount of data based on different contexts. However, collecting the accurate feature and classifying the context into patterns using neural networks algorithms require high time and complexity. Therefore, using deep learning algorithms in integration with neural networks can bring optimize solutions. Consequently, the aim of this chapter is to provide an overview of how the advance deep learning algorithms can be used to solve various existing challenges in Big Data analytics.
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