Big data in transportation: a systematic literature analysis and topic classification (2024)

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Authors: Danai Tzika-Kostopoulou, Eftihia Nathanail, Konstantinos Kokkinos

Knowledge and Information Systems, Volume 66, Issue 8

Pages 5021 - 5046

Published: 08 May 2024 Publication History

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    Abstract

    This paper identifies trends in the application of big data in the transport sector and categorizes research work across scientific subfields. The systematic analysis considered literature published between 2012 and 2022. A total of 2671 studies were evaluated from a dataset of 3532 collected papers, and bibliometric techniques were applied to capture the evolution of research interest over the years and identify the most influential studies. The proposed unsupervised classification model defined categories and classified the relevant articles based on their particular scientific interest using representative keywords from the title, abstract, and keywords (referred to as top words). The model’s performance was verified with an accuracy of 91% using Naïve Bayesian and Convolutional Neural Networks approach. The analysis identified eight research topics, with urban transport planning and smart city applications being the dominant categories. This paper contributes to the literature by proposing a methodology for literature analysis, identifying emerging scientific areas, and highlighting potential directions for future research.

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    Published In

    Big data in transportation: a systematic literature analysis and topic classification (1)

    Knowledge and Information Systems Volume 66, Issue 8

    Aug 2024

    657 pages

    ISSN:0219-1377

    Issue’s Table of Contents

    © The Author(s) 2024.

    Publisher

    Springer-Verlag

    Berlin, Heidelberg

    Publication History

    Published: 08 May 2024

    Accepted: 21 March 2024

    Revision received: 26 January 2024

    Received: 06 August 2023

    Author Tags

    1. Big data
    2. Transportation
    3. Topic model
    4. Classification
    5. Term frequency–inverse document frequency method

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    • Brief-report

    Funding Sources

    • Research, Innovation and Excellence Program of the University of Thessaly.
    • University of Thessaly Central Library

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    Big data in transportation: a systematic literature analysis and topic classification (2)

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