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Exploring Potential Use of Mobile Phone Data Resource to Analyze Inter-regional Travel Patterns in Japan

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Data Mining and Big Data (DMBD 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10387))

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Abstract

In Japan, Inter-Regional Travel Survey gives rich information to researchers and transportation planners. The current survey data was conducted in 2010, and the newest survey data collected in 2015 will be available soon. This national survey is mainly based on the on-site questionnaire survey which requires an enormous budget and spends so much time to finalize and publish the data result. Recently, ubiquitous mobile computing and the big data give us new opportunities for exploring a new type of data resource besides the traditional survey data. This study clarifies the deviation of cell phone data at aggregated origin-destination level of inter-regional trip flows, compared with the traditional on-site passenger survey. Also, the mechanisms of inter-regional trip generation are explained through travel patterns by a classification tree analysis, one of the big data mining classification algorithms.

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Author information

Authors and Affiliations

  1. Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-8527, Japan

    Canh Xuan Do & Makoto Tsukai

Authors
  1. Canh Xuan Do
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  2. Makoto Tsukai
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Corresponding author

Correspondence to Canh Xuan Do .

Editor information

Editors and Affiliations

  1. Peking University, Beijing, China

    Ying Tan

  2. Kyushu University, Fukuoka, Japan

    Hideyuki Takagi

  3. Southern University of Science and Technology, Shenzhen, China

    Yuhui Shi

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Xuan Do, C., Tsukai, M. (2017). Exploring Potential Use of Mobile Phone Data Resource to Analyze Inter-regional Travel Patterns in Japan. In: Tan, Y., Takagi, H., Shi, Y. (eds) Data Mining and Big Data. DMBD 2017. Lecture Notes in Computer Science(), vol 10387. Springer, Cham. https://doi.org/10.1007/978-3-319-61845-6_32

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  • DOI: https://doi.org/10.1007/978-3-319-61845-6_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61844-9

  • Online ISBN: 978-3-319-61845-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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