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Multimedia Data Learning

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Abstract

Multimedia data learning (a.k.a. multimedia data mining) is an emerging, multidisciplinary, and interdisciplinary research area with a wide spectrum of real-world applications related to a wide suite of areas noticeably including machine learning, artificial intelligence, data mining, multimedia, computer vision, and natural language processing. This chapter introduces important and fundamental concepts and theories of this area and provides further references.

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Notes

  1. 1.

    Here we are only concerned with a research area; multimedia may also be referred to industries and even social or societal activities.

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Author information

Authors and Affiliations

  1. Binghamton University, State University of New York, Binghamton, NY, USA

    Zhongfei (Mark) Zhang

  2. Microsoft AI & Research, Sunnyvale, CA, USA

    Zhongfei (Mark) Zhang

  3. Google, Mountain View, CA, USA

    Ruofei (Bruce) Zhang

Authors
  1. Zhongfei (Mark) Zhang
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  2. Ruofei (Bruce) Zhang
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Correspondence to Zhongfei (Mark) Zhang .

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Editors and Affiliations

  1. Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Lior Rokach

  2. Department of Industrial Engineering, Tel Aviv University, Ramat Aviv, Israel

    Oded Maimon

  3. Department of Industrial Engineering, Tel Aviv University, Tel Aviv, Israel

    Erez Shmueli

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Zhang, Z.(., Zhang, R.(. (2023). Multimedia Data Learning. In: Rokach, L., Maimon, O., Shmueli, E. (eds) Machine Learning for Data Science Handbook. Springer, Cham. https://doi.org/10.1007/978-3-031-24628-9_19

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