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A Review of Temporal Network Analysis and Applications

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3D Imaging—Multidimensional Signal Processing and Deep Learning

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 349))

Abstract

With the continuous development of network science, a single and static network structure has become more and more difficult to portray various complex systems, while the temporal network is becoming an effective tool to solve the above problem. At present, the research on the temporal network is still at the stage of primary, and there are still many worthy areas to be further explored. Inspired by this, in our paper, we review the modeling and representation of temporal networks, the structural characteristics and statistical properties of networks, and the application analysis; analyze the weaknesses of the current research; and look forward to the future development aspects.

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Acknowledgements

The authors would like to convey their appreciation for the financial support given by the National Natural Science Foundation and the Project with the National University of Defense and Technology. The authors also agree there has been no conflict of interest in the process of this work.

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Authors and Affiliations

  1. Department of Intelligence, Air Force Early Warning Academy, Wuhan, 430019, Hubei, China

    Jintao Yu & Bing Xiao

  2. Zhejiang Lab, Hangzhou, 311122, China

    Yuzhu Cui

Authors
  1. Jintao Yu
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  2. Bing Xiao
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  3. Yuzhu Cui
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Corresponding author

Correspondence to Jintao Yu .

Editor information

Editors and Affiliations

  1. Interscience Institute of Management and Technology, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  2. Technical University of Sofia, Sofia, Bulgaria

    Roumen Kountchev

  3. Department of Physics, Yunnan Normal University, Kunming, China

    Yonghang Tai

  4. TK Engineering, Sofia, Bulgaria

    Roumiana Kountcheva

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Yu, J., Xiao, B., Cui, Y. (2023). A Review of Temporal Network Analysis and Applications. In: Patnaik, S., Kountchev, R., Tai, Y., Kountcheva, R. (eds) 3D Imaging—Multidimensional Signal Processing and Deep Learning. Smart Innovation, Systems and Technologies, vol 349. Springer, Singapore. https://doi.org/10.1007/978-981-99-1230-8_1

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