Visual Knowledge Discovery from Public Transit Performance Data

Carson K. Leung, Mohammadafaz V. Munshi, Vrushil Kiritkumar Patel, Nhu Minh Ngoc Pham, Yixi Wu

2023 27th International Conference Information Visualisation (IV)(2023)

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摘要
Public transit is an important component of the day-to-day activities of many people. It provides a cost-effective and convenient way for individuals to commute to work, school, and other destinations. Public transit bus is a vital mode of transportation for students, as it enables them to commute to and from their educational institutions. Delays in bus schedules can have severe consequences, such as missing exams, meetings, and other important engagements. Hence, in this paper, we present a visual knowledge discovery solution to mine public transit bus on-time performance data and visualize the mined results. In particular, visual representation (e.g., graphs, time plots) from our visual knowledge discovery process help reveal factors contributing to bus delays in different neighborhood areas. This helps the service providers to improve their services, and thus enhance rider experience. Evaluation on real-life data from a Canadian city shows the practicality of our solution.
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关键词
information visualization,visual knowledge discovery,data science,data visualization,knowledge discovery,transportation data,public transit,bus,on-time performance,bus delay
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