Citation

Al-Dohuki S, Zhao Y, Kamw F, Yang J, Ye X, Chen W. IEEE Comput. Graph. Appl. 2019; ePub(ePub): ePub.

Copyright

(Copyright © 2019, IEEE (Institute of Electrical and Electronics Engineers))

DOI

10.1109/MCG.2019.2911230

PMID

30990422

Abstract

QuteVis uses multi-sketch query and visualization to discover specific times and days in history with specified joint traffic patterns at different city locations. Users can use touch input devices to define, edit, and modify multiple sketches on a city map. A set of visualizations and interactions are provided to help users browse and compare retrieved traffic situations and discover potential influential factors. QuteVis is built upon a transport database that integrates heterogeneous data sources with an optimized spatial indexing and weighted similarity computation. An evaluation with real-world data and domain experts demonstrates that QuteVis is useful in urban transportation applications in modern cities.

Language: en