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Knowledge Discovery: We define "Knowledge Discovery" as the process of generating actionable predictive insights from massive volumes of heterogeneous data to facilitate reliable and real-time decision-making for national and global priorities.
Methodologically, we have focused on analyses of anomalies and unusual behavior, change and change point detection, nonlinear dynamics and chaos, spatiotemporal data mining, as well as complexity and emergence.
Our domains of interest include sensor-based KD, climate extremes, land cover, transportation security and social behavioral emergence.
The following PPT files are included: [1] 5-min Poster Presentation (2 slides); [2] KD at ORNL (README First: Overview); [3] Climate Extremes and Uncertainty (FCF-2008...); [4] Anomaly Analysis (Land Cover and Transportation/Sensors); [5] Social Behavior Analysis (DARPA - HSBC...)
The following websites are included: [1] Climate Change War Game; [2] SensorKDD 2007; [3] SensorKDD 2008; [4] Recorded Presentation at AMS 2008; [5] Session at AGU Joint Assembly 2008; [6] Session at AGU Fall Meeting 2008; [7] Research Website of Auroop Ganguly
Selected publications in climate and hydrology are included
Credits and Disclaimers: The Knowledge Discovery (KD) initiative and research thrust at ORNL are led by the Computational Sciences and Engineering division. This virtual poster is exemplary of ORNL's KD efforts rather than exhaustive.
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