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Using Learning Features to Find Similar Trajectories

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Web Technologies and Applications (APWeb 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9865))

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Abstract

In the last decade, the trajectories data have been collected by many applications and such trajectories contain rich information that can be used to detect events especially for anomaly event detections. However, there are still many challenges on this problem, the major one is how to identify the similar trajectories on semantic level. In this work, we extract the nature features from raw trajectories and use them to do the semantic trajectory similarity search. To achieve this, we propose a PLS algorithm to detect such semantic similar trajectories efficiently and effectively. We also leverage the DBSCAN to help extract the information from large trajectory data. The results of our algorithm are demonstrated by the real world dataset.

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Acknowledgments

The authors would like to acknowledge the support of the project which is provided by the National Natural Science Foundation of China under Grant (No. U1435220)(No. 61503365).

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Authors and Affiliations

  1. Science and Technology on Integrated Information System Laboratory, Institute of Software Chinese Academy of Sciences, Beijing, China

    Peiguo Fu, Xiaohui Hu & Hui Zhang

  2. Pivotal.inc, San Francisco, USA

    Haozhou Wang & Kuien Liu

Authors
  1. Peiguo Fu
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  2. Haozhou Wang
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  3. Kuien Liu
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  4. Xiaohui Hu
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  5. Hui Zhang
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Corresponding author

Correspondence to Peiguo Fu .

Editor information

Editors and Affiliations

  1. University of Tsukuba , Tsukuba, Japan

    Atsuyuki Morishima

  2. East China Normal University , Shanghai, China

    Rong Zhang

  3. University of New South Wales , Sydney, New South Wales, Australia

    Wenjie Zhang

  4. The University of New South Wales, School of Computer Science and Engineering, Sydney, Australia

    Lijun Chang

  5. Advanced Digital Sciences Center, Illinois at Singapore Pte Ltd, Advanced Digital Sciences Center, Fusionopolies Way, Singapore

    Tom Z. J Fu

  6. Hyundai Motor Tower, Pivotal Inc 15/F, Hyundai Motor Tower, Chaoyang, China

    Kuien Liu

  7. Illinois at Singapore Pte Ltd, Advanced Digital Sciences Center , Singapore, Singapore

    Xiaoyan Yang

  8. South China Normal University, School of Computer Science, Guangzhou, China

    Jia Zhu

  9. Department of Computer Science, Hong Kong Baptist University Department of Computer Science, Kowloon Tong, Hong Kong

    Zhiwei Zhang

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© 2016 Springer International Publishing Switzerland

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Fu, P., Wang, H., Liu, K., Hu, X., Zhang, H. (2016). Using Learning Features to Find Similar Trajectories. In: Morishima, A., et al. Web Technologies and Applications. APWeb 2016. Lecture Notes in Computer Science(), vol 9865. Springer, Cham. https://doi.org/10.1007/978-3-319-45835-9_26

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  • DOI: https://doi.org/10.1007/978-3-319-45835-9_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45834-2

  • Online ISBN: 978-3-319-45835-9

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