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Understanding Places Exploration and Visitation via Human Mobility Mining

Author

Listed:
  • Shafqat Shad

    (Univeristy of Montevallo, USA)

  • Muhammad Usman

    (Verizon Wireless, USA)

  • Chandan Kumar

    (Iowa State University, USA)

  • Hadiqa Afzal

    (University of Montevallo, USA)

Abstract
Spatial-temporal data is widely available because of advancement in location acquisition technologies (GPS, GSM, Wifi, etc.) over past decades. This spatial-temporal data can easily be used to leverage user's trajectories, history, and habits to develop location-based services (LBS). But to leverage user's history based on location is bit challenging, in this paper we used the user's GPS log data to discover trajectories and analyze different life patterns over it. We proposed that a human spends 80% of his life on known places or safe places. We converted GPS patterns into visitation locations, converted them into daily and periodic trends and analyzed them over time to prove our assumption. We used the GPS data collected by Microsoft Research Asia, this data has 182 users with 73 users with their mode of movement information i.e., Taxi, Walk, Train etc.

Suggested Citation

  • Shafqat Shad & Muhammad Usman & Chandan Kumar & Hadiqa Afzal, 2024. "Understanding Places Exploration and Visitation via Human Mobility Mining," International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 20(1), pages 1-16, January.
    • Handle: RePEc:igg:jiit00:v:20:y:2024:i:1:p:1-16
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    References listed on IDEAS

    as
    1. Kasin Ransikarbum & Scott J. Mason, 2022. "A bi-objective optimisation of post-disaster relief distribution and short-term network restoration using hybrid NSGA-II algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 60(19), pages 5769-5793, October.
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