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  1. Survey paper

    Big data analytics: a survey

    Chun-Wei Tsai, Chin-Feng Lai, Han-Chieh Chao and Athanasios V. Vasilakos

    Published on: 1 October 2015

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Aims and scope

The Journal of Big Data publishes high-quality, scholarly research papers, methodologies and case studies covering a broad range of topics, from big data analytics to data-intensive computing and all applications of big data research. The journal examines the challenges facing big data today and going forward including, but not limited to: data capture and storage; search, sharing, and analytics; big data technologies; data visualization; architectures for massively parallel processing; data mining tools and techniques; machine learning algorithms for big data; cloud computing platforms; distributed file systems and databases; and scalable storage systems. Academic researchers and practitioners will find the Journal of Big Data to be a seminal source of innovative material.

Open Article Collection

Big Data and Smart Computing
Lead Guest Editor:
Wookey Lee, INHA University, Korea
Guest Editor:
Cyrus Shahabi, University of Southern California, USA

About SpringerOpen

SpringerOpen is Springer’s new suite of open access journals which will cover all disciplines. SpringerOpen journals are fully and immediately open access and will publish articles under the Creative Commons Attribution license. This makes it easy for authors to fully comply with open access mandates and retain copyright. SpringerOpen journals combine open access and our expertise in delivering high-quality and rapid publications, from online submission systems and in-depth peer review to an efficient, author-friendly production process.

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Journal of Big Data Accepted into Scopus!

We are pleased to announce that the Journal of Big Data has been accepted into Scopus, the world's largest abstract and citation database of peer-reviewed literature. Previously published articles will appear in Scopus in the coming months.