Textual Data in Transportation Research: Techniques and Opportunities

Aseem Kinra, Samaneh Beheshti-Kashi, Francisco Câmara Pereira, François Combes, Werner Rothengatter

Publikation: Bidrag til bog/antologi/rapportBidrag til bog/antologiForskningpeer review


Transportation is rich in human communication. Travellers often use information services, interact with each other and with transport providers through natural language. And the transport providers and regulators (traffic managers, police, transit operators, etc.) need to constantly communicate to coordinate, plan and inform each other. This generates substantial amounts of structured, semistructured or unstructured data, generated within or outside of an organization's boundary. Such data is often rich in information that becomes absent, or oversimplified e.g., aggregated into dummy variables, in actual research or practical applications. If a researcher could transform such richer data into meaningful variables in her models, new opportunities would arise for e.g., better coping with heterogeneity or random effects. Due to recent advances in computational text analysis, textual data have become utilizable to a much higher degree. The objective of this chapter is to introduce techniques for textual data processing, and provide some recent application examples in transportation research.
TitelMobility Patterns, Big Data and Transport Analytics : Tools and Applications for Modeling
RedaktørerConstantinos Antoniou, Loukas Dimitriou, Francisco Pereira
Antal sider25
Udgivelses stedAmsterdam
ISBN (Trykt)9780128129708
ISBN (Elektronisk)9780128129715
StatusUdgivet - 2019

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Kinra, A., Beheshti-Kashi, S., Pereira, F. C., Combes, F., & Rothengatter, W. (2019). Textual Data in Transportation Research: Techniques and Opportunities. I C. Antoniou, L. Dimitriou, & F. Pereira (red.), Mobility Patterns, Big Data and Transport Analytics: Tools and Applications for Modeling (s. 173-197). Elsevier. https://doi.org/10.1016/B978-0-12-812970-8.00008-7