Personalization in Public Transport Passenger Information Systems: A Systematic Review and Framework

IF 23.8 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS ACM Computing Surveys Pub Date : 2025-03-06 DOI:10.1145/3721478
Marloes Vredenborg, Anouk van Kasteren, Judith Masthoff
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引用次数: 0

Abstract

In recent years, efforts to promote public transport usage have emphasized the integration of personalization into passenger information systems. Whilst numerous studies have explored this topic, a comprehensive overview of the state-of-the-art remains absent. To address this gap, we systematically reviewed 91 research papers published between 2000 and October 2024. Based on our review, we introduce a comprehensive framework that organizes the field along three key dimensions: personalization objects, attributes, and evaluation. Furthermore, we provide valuable insights for researchers and practitioners engaged in the study, design, and development of personalized passenger information systems and identify research opportunities to guide future advancements in the field.
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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