Publication Type
Conference Proceeding Article
Version
submittedVersion
Publication Date
5-2014
Abstract
Mining trajectory datasets has many important applications. Real trajectory data often involve uncertainty due to inadequate sampling rates and measurement errors. For some trajectories, their precise positions cannot be recovered and the exact routes that vehicles traveled cannot be accurately reconstructed. In this paper, we investigate the uncertainty problem in trajectory data and present a visual analytics system to reveal, analyze, and solve the uncertainties associated with trajectory samples. We first propose two novel visual encoding schemes called the road map analyzer and the uncertainty lens for discovering road map errors and visually analyzing the uncertainty in trajectory data respectively. Then, we conduct three case studies to discover the map errors, to address the ambiguity problem in map-matching, and to reconstruct the trajectories with historical data. These case studies demonstrate the capability and effectiveness of our system.
Keywords
Uncertainty, trajectory, visual analysis
Discipline
Computer Sciences | Databases and Information Systems
Publication
Advances in Knowledge Discovery and Data Mining: 18th Pacific-Asia Conference, PAKDD 2014, Tainan, Taiwan, May 13-16, 2014. Proceedings, Part I
Volume
842
First Page
509
Last Page
520
ISBN
978-3-319-06608-0
Identifier
10.1007/978-3-319-06608-0_42
Publisher
Springer
Citation
LU, Lu; CAO, Nan; LIU, Siyuan; NI, Lionel; YUAN, Xiaoru; and QU, Huamin.
Visual Analysis of Uncertainty in Trajectories. (2014). Advances in Knowledge Discovery and Data Mining: 18th Pacific-Asia Conference, PAKDD 2014, Tainan, Taiwan, May 13-16, 2014. Proceedings, Part I. 842, 509-520.
Available at: https://ink.library.smu.edu.sg/sis_research/3480
Copyright Owner and License
LARC
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.