Efficient Location Sampling Algorithms for Road Networks
Authors: 
Sara Ahmadian, Sreenivas Gollapudi, Kostas Kollias, Vivek Kumar, Ameya Velingker, Santhoshini VelusamyAuthors Info & Claims
Sara Ahmadian, Sreenivas Gollapudi, Kostas Kollias, Vivek Kumar, Ameya Velingker, Santhoshini VelusamyAuthors Info & ClaimsPages 899 - 902
Abstract
Many geographic information systems applications rely on data provided by user devices in the road network, including traffic monitoring, driving navigation, and road closure detection. The underlying signal is generally collected by sampling locations from user trajectories. The sampling process, though critical for various applications, has not been studied sufficiently in the literature. While the most natural way to sample a trajectory may be to use a frequency based algorithm, e.g., sampling locations every x seconds, such a sampling strategy can be quite wasteful in resources (e.g., server-side processing, user battery) as well as stored user data. In this work, we conduct a horizontal study of various location sampling algorithms (based on frequency, road geography, reservoir sampling, etc.) and assess their trade-offs in terms of the size of the stored data and the induced quality of training for prediction tasks (specifically predicting speeds on road segments).
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- Efficient Location Sampling Algorithms for Road Networks
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May 2024
1928 pages
ISBN:9798400701726
DOI:10.1145/3589335
- General Chairs:
- Tat-Seng Chua,
- Chong-Wah Ngo,
- Program Chairs:
- Ravi Kumar,
- Hady W. Lauw,
- Roy Ka-Wei Lee
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Published: 13 May 2024
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