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Research Thrust

Rapid Detection of Emerging Pattern

Data mining algorithms at the Auton Lab have successfully detected new emerging patterns in various domains: Health services, Agriculture, and Manufacturing and Oil companies. Our algorithms are 10-1000 times faster than other traditional techniques. The results demonstrate significantly higher detection power with much smaller false positive rates. We have applied these algorithms in semi/fully-automated modes under supervied/unsupervised environments and for retrospective/prospective surveillance. A few algorithms for Rapid detection of emerging patterns are: WSARE, Ultra Fast SSS, and TipMon.

Paper

Name	Authors	Actions
A Bayesian scan statistic for spatial cluster detection	Daniel Neill, Andrew Moore, Gregory Cooper	show
A Bayesian spatial scan statistic	Daniel Neill, Andrew Moore, Gregory Cooper	show
A Fast Multi-Resolution Method for Detection of Significant Spatial Disease Clusters	Daniel Neill, Andrew Moore	show
A Fast Multi-Resolution Method for Detection of Significant Spatial Overdensities	Daniel Neill, Andrew Moore	show
A Study into Detection of Bio-Events in Multiple Streams of Surveillance Data	Josep Roure, Artur Dubrawski, Jeff Schneider	show
Bayesian Network Anomaly Pattern Detection for Disease Outbreaks	Weng-Keen Wong, Andrew Moore, Gregory Cooper, Michael Wagner	show
Detecting Anomalous Patterns in Pharmacy Retail Data	Robin Sabhnani, Daniel Neill, Andrew Moore	show
Detecting Significant Multidimensional Spatial Clusters	Daniel Neill, Andrew Moore	show
Efficient Algorithms for Non-Parametric Clustering with Clutter	Weng-Keen Wong, Andrew Moore	show
Efficient Analytics for Effective Monitoring of Biomedical Security	Robin Sabhnani, Daniel B. Neill, Andrew W. Moore, Artur W. Dubrawski, Weng-Keen Wong	show
Monitoring Food Safety by Detecting Patterns in Consumer Complaints	Artur Dubrawski, Kimberly Elenberg, Andrew Moore, Maheshkumar Sabhnani	show
Optimal Reinsertion: A new search operator for accelerated and more accurate Bayesian network structure learning	Andrew Moore, Weng-Keen Wong	show
Rapid Detection of Significant Spatial Clusters	Daniel Neill, Andrew Moore	show
Rule-based Anomaly Pattern Detection for Detecting Disease Outbreaks	Weng-Keen Wong, Andrew Moore, Gregory Cooper, Michael Wagner	show
Summary of Biosurveillance-relevant statistical and data mining technologies	Andrew Moore, Gregory Cooper, Rich Tsui, Michael Wagner	show
What's Strange About Recent Events	Weng-Keen Wong, Andrew Moore, Gregory Cooper, Michael Wagner	show

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