Travel Time Estimation Using NiagaraST and latte
Summary: latte extends stream processing to support stream-archive queries over live traffic streams and large historical archives (PORTAL). Travel-time estimation demo uses NiagaraST-based latte to show stream-archive joins and aggregations for ITS data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Kristin Tufte (Portland State University)
- 2. Jin Li (Portland State University)
- 3. David Maier (Portland State University)
- 4. Vassilis Papadimos (Portland State University)
- 5. Robert L. Bertini (Portland State University)
- 6. James Rucker (Portland State University)
BibTeX Citation
@inproceedings{tufte_sigmod07,
title = {{Travel Time Estimation Using NiagaraST and latte}},
author = {Tufte, Kristin and Li, Jin and Maier, David and Papadimos, Vassilis and Bertini, Robert L. and Rucker, James},
series = {{SIGMOD} '07},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1247480.1247617},
url = {https://dl.acm.org/doi/10.1145/1247480.1247617},
year = {2007}
}Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,463 | Consistency in a Stream Warehouse | 2011 | CIDR | 6.6860367e-05 |
| 9,258 | Data Stream Warehousing in Tidalrace | 2015 | CIDR | 5.29708e-05 |
| 9,318 | Estimating Quantiles from the Union of Historical and Streaming Data | 2017 | VLDB | 5.289545e-05 |
| 10,677 | RLER-TTE: An Efficient and Effective Framework for En Route Travel Time Estimation with Reinforcement Learning | 2025 | SIGMOD | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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