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Sixth
International Workshop on Knowledge |
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To be held in conjunction with |
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Sensor-KDD '12 Workshop |
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August
12, 2012
Beijing, China. |
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Submissions | ||||||||||
Challenge Problem Description For the second SensorKDD Challenge, to be held in conjunction with the 6th Workshop on Knowledge Discovery from Sensor Data (SensorKDD-2012), we pose a general and open-ended problem related to the workshop theme Climate Change, Energy Assurance, and Infrastructural Impacts. Specifically, we focus on the first component and provide a large climate dataset consisting of both model simulated and observed precipitation for a period of time. Your task is to detect significant trends in the precipitation extremes. Note that the notion of extremes is open to interpretation and you are free to consider multiple indicator of extremes. We omit a precise definition here to invite creative problem definitions and solutions. Data Following is a short description of the model simulated and observed data.
Submissions We invite the submission of manuscripts addressing this challenge task following the format of the SensorKDD-2012 Workshop (maximum 9 pages, ACM standard format). Please include your definition of extremes. Entries will be evaluated subjectively based on their methodology and validation strategy. The deadline for submission is 30th May. Please email your submission to Sensorkdd2012@gmail.com with a subject "SensorKDD Challenge" and include your name, affiliations and contact details. Award Best Challenge Entry Award. Contact Information For questions about the challenge or to inquire about additional climate datasets, please contact: Debasish Das Challenge Organizers Debasish Das, Northeastern University,
Boston, MA and Temple University, Philadelphia, PA, USA. References: [1] Kao, S.-C. and A. R. Ganguly (2011), Intensity, duration, and frequency of precipitation extremes under 21st-century warming scenarios, Journal of Geophysical Research - Atmospheres, 116, D16119. [2] Ghosh, S., D. Das, S.-C. Kao, A. R. Ganguly (2012), Lack of uniform trends but increasing spatial variability in observed Indian rainfall extremes, Nature Climate Change. [3] IPCC Climate model datasets hosted in PCMDI. http://www-pcmdi.llnl.gov/ipcc/about_ipcc.php.
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Travel Information |
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Datastreams Mining in Wikipedia |
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SDS Lab @ NEU | ||||||||||
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