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FASTS: A Satisfaction-Boosting Bus Scheduling Assistant

conference contribution
posted on 2024-11-03, 12:56 authored by Songsong Mo, Zhifeng Bao, Baihua Zheng, Zhiyong Peng
In this paper, we demonstrate a satisfaction-boosting bus scheduling assistant called FASTS, which assists users to find an optimal bus schedule. FASTS performs bus scheduling based on the constraints specified by the user in either a coarse-grained or a fine-grained manner, supports different explorations with a varying number of constraints, and provides analysis to quantify the performance of bus schedules and presents the results in a visually pleasing way. We demonstrate FASTS using real-world bus routes (396 routes) and one-week bus touch-on/touch-off records (28 million trip records) in Singapore.

Funding

Continuous intent tracking for virtual assistance using big contextual data

Australian Research Council

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Next-generation Intelligent Explorations of Geo-located Data

Australian Research Council

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History

Related Materials

  1. 1.
    DOI - Is published in 10.14778/3415478.3415497
  2. 2.
    ISSN - Is published in 21508097

Start page

2873

End page

2876

Total pages

4

Outlet

Proceedings of the 46th International Conference on Very Large Data Bases  (VLDB 2020)

Name of conference

VLDB 2020

Publisher

VLDB Endowment

Place published

New York, United States

Start date

2020-08-31

End date

2020-09-04

Language

English

Copyright

© This work is licensed under the Creative Commons AttributionNonCommercial-NoDerivatives 4.0 International License.

Former Identifier

2006102051

Esploro creation date

2020-10-28

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