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International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems

IEA/AIE 2016: Trends in Applied Knowledge-Based Systems and Data Science pp 725–736Cite as

Multivariate Higher Order Information for Emergency Management Based on Tourism Trajectory Datasets

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9799))

Abstract

Higher order information of trajectory dataset for “what-if” analysis is getting more popular for providing better informed decision making. However, existing research had been studied trajectory higher order information based on univariate dataset only. There is yet no research to study higher order information of multivariate dataset for trajectory analysis. This paper will introduce a unified data structure which supports multivariate datasets for trajectory analysis and approaches to analyse information based on multivariate higher order information for making decisions related to emergency management. Interactive visualisation tools are implemented to facilitate the analysis. Tourism trajectory dataset is used to demonstrate the proposed approach.

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Author information

Authors and Affiliations

  1. Information Technology Academy, College of Business, Law and Governance, James Cook University, Cairns, QLD, 4870, Australia

    Ye Wang, Kyungmi Lee & Ickjai Lee

Authors
  1. Ye Wang
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  2. Kyungmi Lee
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  3. Ickjai Lee
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Corresponding author

Correspondence to Ickjai Lee .

Editor information

Editors and Affiliations

  1. Iwate Prefectural University , Iwate, Japan

    Hamido Fujita

  2. Department Computer Science, Texas State University, San Marcos, Texas, USA

    Moonis Ali

  3. Universiti Teknologi Malaysis (UTM), Bahru, Malaysia

    Ali Selamat

  4. Iwate Prefectural University , Iwate, Japan

    Jun Sasaki

  5. Iwate Prefectural University , Iwate, Japan

    Masaki Kurematsu

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© 2016 Springer International Publishing Switzerland

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Wang, Y., Lee, K., Lee, I. (2016). Multivariate Higher Order Information for Emergency Management Based on Tourism Trajectory Datasets. In: Fujita, H., Ali, M., Selamat, A., Sasaki, J., Kurematsu, M. (eds) Trends in Applied Knowledge-Based Systems and Data Science. IEA/AIE 2016. Lecture Notes in Computer Science(), vol 9799. Springer, Cham. https://doi.org/10.1007/978-3-319-42007-3_62

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  • DOI: https://doi.org/10.1007/978-3-319-42007-3_62

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42006-6

  • Online ISBN: 978-3-319-42007-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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