A holistic data-driven framework for developing a complete profile of bus passengers

User profiles, considered as one of the fundamental inputs of recommendation systems and customized services, can be rationally applied in the public transport domain to represent passengers’ characteristics and behavioral preferences. A user profile of a bus passenger, termed as a bus passenger profile (BPP), is an assortment of labels containing passengers’ travel features. This paper proposes a data-driven framework for developing BPP so as to provide guidance on how to create and estimate user profiles for bus passengers based on smart card data. The proposed method comprises three steps. (i) Data preprocessing aimed at extracting key information and preparing passenger profiling. (ii) A tag system aimed at storing the estimated travel features of passengers. (iii) Knowledge graphs aimed at connecting various BPP with semantic edges for practical application of prior knowledge in downstream tasks. The developed framework is implemented in a case study of the Beijing bus system. Deployment of the developed framework has demonstrated that it can satisfactorily develop BPP, while prior knowledge from the BPP-based knowledge graphs can benefit downstream tasks.

• Record URL:
  • https://doi.org/10.1016/j.tra.2023.103692
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S096585642300112X
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/09658564
• Supplemental Notes:
  • © 2023 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Chen, Siyuan
  • Liu, Xin
  • Lyu, Cheng
  • Vlacic, Ljubo
  • Tang, Tianli
  • Liu, Zhiyuan
• Publication Date: 2023-7

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 103692
• Serial:
  • Transportation Research Part A: Policy and Practice
  • Volume: 173
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0965-8564
  • Serial URL: http://www.sciencedirect.com/science/journal/09658564

Subject/Index Terms

• TRT Terms: Behavior; Data mining; Information, data, and knowledge; Passengers; Persons and personal characteristics; Smart cards; Transit buses
• Geographic Terms: Beijing (China)
• Subject Areas: Data and Information Technology; Highways; Passenger Transportation; Public Transportation;

Filing Info

• Accession Number: 01889707
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 7 2023 1:52PM