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CBOW and LSTM Based User Mobile Trajectory Prediction

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Machine Learning for Cyber Security (ML4CS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12488))

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Abstract

Trajectory prediction of mobile object has been a hotspot in current research. Many current mobile object trajectory models treat locations as isolated points, which do not suitable for scenes with a large number of locations and ignore the relationship between the locations. In order to reduce the dimension of location and obtain the movement pattern, we apply the Continuous-valued word representations (CBOW) word embedding method in natural language processing to represent the urban position. At the same time, the Long Short Term Memory (LSTM) model is established in combination with the historical position of the user to predict the next position of the user. Experiments show that the investigations in this paper can improve the prediction accuracy.

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Acknowledgments

This work was supported in part by the Natural Science Foundation of Guangdong Province (Grant No. 2018A030313014), the Guangdong University Key Project (2019KZDXM012), and the research team project of Dongguan University of Technology (Grant No. TDY-B2019009).

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Authors and Affiliations

  1. School of Computer, Guangdong University of Technology, Guangzhou, People’s Republic of China

    Geng Sun

  2. School of Computer Science and Technology, Dongguan University of Technology, Dongguan, People’s Republic of China

    Ming Tao

  3. Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, 510006, People’s Republic of China

    Ming Tao

Authors
  1. Geng Sun
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  2. Ming Tao
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Corresponding author

Correspondence to Ming Tao .

Editor information

Editors and Affiliations

  1. Xidian University, Xi'an, China

    Xiaofeng Chen

  2. Guangzhou University, Guangzhou, China

    Hongyang Yan

  3. Michigan State University, East Lansing, MI, USA

    Qiben Yan

  4. Division of Computer, Electrical and Mathematical Sciences and Engineering, King Abdullah University of Science, Thuwal, Saudi Arabia

    Xiangliang Zhang

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Sun, G., Tao, M. (2020). CBOW and LSTM Based User Mobile Trajectory Prediction. In: Chen, X., Yan, H., Yan, Q., Zhang, X. (eds) Machine Learning for Cyber Security. ML4CS 2020. Lecture Notes in Computer Science(), vol 12488. Springer, Cham. https://doi.org/10.1007/978-3-030-62463-7_7

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  • DOI: https://doi.org/10.1007/978-3-030-62463-7_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62462-0

  • Online ISBN: 978-3-030-62463-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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