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Investigation on Deep Learning Approach for Big Data: Applications and Challenges
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Author(s): Dharmendra Singh Rajput (VIT University, India), T. Sunil Kumar Reddy (Sri Venkateswara College of Engineering and Technology, India)and Dasari Naga Raju (Sri Venkateswara College of Engineering and Technology, India)
Copyright: 2018
Pages: 14
Source title:
Handbook of Research on Pattern Engineering System Development for Big Data Analytics
Source Author(s)/Editor(s): Vivek Tiwari (International Institute of Information Technology, India), Ramjeevan Singh Thakur (Maulana Azad National Institute of Technology, India), Basant Tiwari (Hawassa University, Ethiopia)and Shailendra Gupta (AISECT University, India)
DOI: 10.4018/978-1-5225-3870-7.ch002
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Abstract
In recent years, big data analytics is the major research area where the researchers are focused. Complex structures are trained at each level to simplify the data abstractions. Deep learning algorithms are one of the promising researches for automation of complex data extraction from large data sets. Deep learning mechanisms produce better results in machine learning, such as computer vision, improved classification modelling, probabilistic models of data samples, and invariant data sets. The challenges handled by the big data are fast information retrieval, semantic indexing, extracting complex patterns, and data tagging. Some investigations are concentrated on integration of deep learning approaches with big data analytics which pose some severe challenges like scalability, high dimensionality, data streaming, and distributed computing. Finally, the chapter concludes by posing some questions to develop the future work in semantic indexing, active learning, semi-supervised learning, domain adaptation modelling, data sampling, and data abstractions.
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