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Precise sensitivity recognizing, privacy preserving, knowledge graph-based method for trajectory data publication

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Acknowledgements

This work was supported in part by the Guangxi “Bagui Schola” Teams and the Guangxi Natural Science Foundation (2020JJA170023).

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Authors and Affiliations

  1. Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin, 541004, China

    Xianxian Li & Li-e Wang

  2. College of Computer Science and Information Engineering, Guangxi Normal University, Guilin, 541004, China

    Xianxian Li, Bing Cai & Li-e Wang

  3. Nanning Tiancheng Zhiyuan Intellectual Property Service Co. Ltd., Nanning, 530000, China

    Lei Lei

Authors
  1. Xianxian Li
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  2. Bing Cai
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  3. Li-e Wang
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  4. Lei Lei
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Corresponding authors

Correspondence to Li-e Wang or Lei Lei.

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The supporting information is available online at journal.hep.com.cn and link.springer.com.

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Li, X., Cai, B., Wang, Le. et al. Precise sensitivity recognizing, privacy preserving, knowledge graph-based method for trajectory data publication. Front. Comput. Sci. 16, 164816 (2022). https://doi.org/10.1007/s11704-021-0417-6

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  • DOI: https://doi.org/10.1007/s11704-021-0417-6

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