Uncertainty in Artificial Intelligence
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Prediction, Expectation, and Surprise: Methods, Designs, and Study of a Deployed Traffic Forecasting Service
Eric Horvitz, Johnson Apacible, Raman Sarin, Lin Liao
Abstract:
We present research on developing models that forecast traffic flow and congestion in the Greater Seattle area. The research has led to the deployment of a service named JamBayes, that is being actively used by over 2,500 users via smartphones and desktop versions of the system. We review the modeling effort and describe experiments probing the predictive accuracy of the models. Finally, we present research on building models that can identify current and future surprises, via efforts on modeling and forecasting unexpected situations.
Keywords:
Pages: 275-283
PS Link:
PDF Link: /papers/05/p275-horvitz.pdf
BibTex:
@INPROCEEDINGS{Horvitz05,
AUTHOR = "Eric Horvitz and Johnson Apacible and Raman Sarin and Lin Liao",
TITLE = "Prediction, Expectation, and Surprise: Methods, Designs, and Study of a Deployed Traffic Forecasting Service",
BOOKTITLE = "Proceedings of the Twenty-First Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-05)",
PUBLISHER = "AUAI Press",
ADDRESS = "Arlington, Virginia",
YEAR = "2005",
PAGES = "275--283"
}


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