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Modeling Travel Behavior Similarity with Trajectory Embedding

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Database Systems for Advanced Applications (DASFAA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10827))

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Abstract

The prevalence of GPS-enabled devices and wireless communication technologies has led to myriads of spatial trajectories describing the movement history of moving objects. While a substantial research effort has been undertaken on the spatio-temporal features of trajectory data, recent years have witnessed the flourish of location-based web applications (i.e., Foursquare, Facebook), enriching the traditional trajectory data by associating locations with activity information, called activity trajectory. These trajectory data contain a wealth of activity information and offer unprecedented opportunities for heightening our understanding about human behaviors. In this paper, we propose a novel framework, called TEH (Trajectory Embedding and Hashing), to mine the similarity among users based on their activity trajectories. Such user similarity is of great importance for individuals to effectively retrieve the information with high relevance. With the time being separated into several slots according to the activity-based temporal distribution, we utilize trajectory embedding technique to mine the sequence property of the activity trajectories by treating them as paragraphs. Then a hash-based method is presented to reduce the dimensions for improving the efficiency of users’ similarity calculation. Finally, extensive experiments on a real activity trajectory dataset demonstrate the effectiveness and efficiency of the proposed methods.

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Notes

  1. 1.

    http://www.foursquare.com.

  2. 2.

    http://www.facebook.com.

  3. 3.

    http://www.flickr.com.

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Acknowledgement

This research is partially supported by the Natural Science Foundation of China (Grant Nos. 61502324, 61532018).

Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Soochow University, Suzhou, China

    Wenyan Yang, Yan Zhao & Guanfeng Liu

  2. School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China

    Bolong Zheng

  3. Aalborg University, Aalborg, Denmark

    Bolong Zheng

  4. Big Data Research Center, University of Electronic Science and Technology ofChina, Chengdu, China

    Kai Zheng

Authors
  1. Wenyan Yang
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  2. Yan Zhao
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  3. Bolong Zheng
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  4. Guanfeng Liu
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  5. Kai Zheng
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Corresponding author

Correspondence to Bolong Zheng .

Editor information

Editors and Affiliations

  1. Simon Fraser University, Burnaby, BC, Canada

    Jian Pei

  2. Aristotle University of Thessaloniki, Thessaloniki, Greece

    Yannis Manolopoulos

  3. University of Queensland, Brisbane, QLD, Australia

    Shazia Sadiq

  4. University of Western Australia, Crawley, WA, Australia

    Jianxin Li

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Yang, W., Zhao, Y., Zheng, B., Liu, G., Zheng, K. (2018). Modeling Travel Behavior Similarity with Trajectory Embedding. In: Pei, J., Manolopoulos, Y., Sadiq, S., Li, J. (eds) Database Systems for Advanced Applications. DASFAA 2018. Lecture Notes in Computer Science(), vol 10827. Springer, Cham. https://doi.org/10.1007/978-3-319-91452-7_41

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  • DOI: https://doi.org/10.1007/978-3-319-91452-7_41

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  • Print ISBN: 978-3-319-91451-0

  • Online ISBN: 978-3-319-91452-7

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