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Multimodal Information Processing and Big Data Analytics in a Digital World

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Multimodal Analytics for Next-Generation Big Data Technologies and Applications

Abstract

This chapter presents a review of important issues for multimodal information processing and Big data analytics in a digital world, emphasizing the issues brought by the concept of universal machine learning intelligence and data-from-everywhere, and driven by the applications for the future and next-generation technologies. Furthermore, the chapter explains the organization of the book, describing which issues and related technologies are addressed in which chapters of the book.

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Authors and Affiliations

  1. School of Computing and Mathematics, Charles Sturt University, Sydney, NSW, Australia

    Kah Phooi Seng

  2. School of Information and Communication Technology, Griffith University, Nathan, QLD, Australia

    Li-minn Ang & Alan Wee-Chung Liew

  3. University of Sydney Business School, University of Sydney, Sydney, NSW, Australia

    Junbin Gao

Authors
  1. Kah Phooi Seng
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  2. Li-minn Ang
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  3. Alan Wee-Chung Liew
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  4. Junbin Gao
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Corresponding author

Correspondence to Kah Phooi Seng .

Editor information

Editors and Affiliations

  1. School of Engineering and Information Technology, University of New South Wales, Canberra, ACT, Australia

    Kah Phooi Seng

  2. School of Information and Communication Technology, Griffith University, Gold Coast, QLD, Australia

    Li-minn Ang

  3. School of Information and Communication Technology, Griffith University, Gold Coast, QLD, Australia

    Alan Wee-Chung Liew

  4. The University of Sydney Business School, University of Sydney, Sydney, NSW, Australia

    Junbin Gao

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© 2019 Springer Nature Switzerland AG

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Seng, K.P., Ang, Lm., Liew, A.WC., Gao, J. (2019). Multimodal Information Processing and Big Data Analytics in a Digital World. In: Seng, K., Ang, Lm., Liew, AC., Gao, J. (eds) Multimodal Analytics for Next-Generation Big Data Technologies and Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-97598-6_1

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  • DOI: https://doi.org/10.1007/978-3-319-97598-6_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-97597-9

  • Online ISBN: 978-3-319-97598-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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