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Administrative Regions Discovery Based on Human Mobility Patterns and Spatio-Temporal Clustering

Author

Listed:
  • Miguel Núñez del Prado

    (Universidad del Pacífico)

  • Hugo Alatrista-Salas

    (Universidad del Pacífico)

Abstract

Currently, the understanding of the human mobility is an important challenge that has a large number of applications, especially in the study of a nations ability to thrive economically and socially. Some works have shown that, it is possible to observe developed and developing countries reviewing their administrative regions borders, in order to reduce costs, or to solve ethnic claims and/or independence movements. In this context, the present work leverages mobile phone data to analyze human mobility patterns. Specifically, we propose a new method to detect administrative regions and paths of interaction between regions, both relying on subscribers mobility patterns extracted from Call Detail Records (CDR). Thus, our method offers a different point of view to redefine administrative boundaries.

Suggested Citation

  • Miguel Núñez del Prado & Hugo Alatrista-Salas, 2016. "Administrative Regions Discovery Based on Human Mobility Patterns and Spatio-Temporal Clustering," Working Papers 16-23, Centro de Investigación, Universidad del Pacífico.
  • Handle: RePEc:pai:wpaper:16-23
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    Cited by:

    1. Linus W. Dietz & Avradip Sen & Rinita Roy & Wolfgang Wörndl, 2020. "Mining trips from location-based social networks for clustering travelers and destinations," Information Technology & Tourism, Springer, vol. 22(1), pages 131-166, March.

    More about this item

    Keywords

    Mobility model; Mobility Markov chain; administrative region; clustering; region interactions;
    All these keywords.

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