TY - GEN
T1 - A non-numerical predictive model for asymmetric analysis
AU - Valenzuela, Michael L.
AU - Feng, Chuan
AU - Reddy, Praneel
AU - Momen, Faisal
AU - Rozenblit, Jerzy W.
AU - Eyck, Brian Ten
AU - Szidarovszky, Ferenc
PY - 2010
Y1 - 2010
N2 - Predicting asymmetric threats (e.g., terrorist events) is becoming ever more important. Prior works have focused on tactical, statistical, and data-fusion systems. The thrust of our work has been the development of a non-numerical predictive model for amplifying intelligence analysts' recognition of emergent threats. The intelligence community uses a Template schema for assessing courses of action. Our predictive model processes non-numerical data to arrive at automated assessment and confidence scores for these Templates. The predictive model is traceable, transparent, and utilizes Human-in-the-Loop data-fusion. For future work, this predictive model will be further enhanced with behavioral filtering. Behavioral filtering adjusts the assessment and confidence of the predictions by intelligently evaluating characteristic behavioral data. This non-numerical predictive model has been tested and verified in the Asymmetric Threat Response and Analysis Program (ATRAP).
AB - Predicting asymmetric threats (e.g., terrorist events) is becoming ever more important. Prior works have focused on tactical, statistical, and data-fusion systems. The thrust of our work has been the development of a non-numerical predictive model for amplifying intelligence analysts' recognition of emergent threats. The intelligence community uses a Template schema for assessing courses of action. Our predictive model processes non-numerical data to arrive at automated assessment and confidence scores for these Templates. The predictive model is traceable, transparent, and utilizes Human-in-the-Loop data-fusion. For future work, this predictive model will be further enhanced with behavioral filtering. Behavioral filtering adjusts the assessment and confidence of the predictions by intelligently evaluating characteristic behavioral data. This non-numerical predictive model has been tested and verified in the Asymmetric Threat Response and Analysis Program (ATRAP).
KW - ATRAP
KW - Data-fusion
KW - Non-numerical
KW - Prediction
KW - Template
UR - http://www.scopus.com/inward/record.url?scp=77953204540&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77953204540&partnerID=8YFLogxK
U2 - 10.1109/ECBS.2010.44
DO - 10.1109/ECBS.2010.44
M3 - Conference contribution
AN - SCOPUS:77953204540
SN - 9780769540054
T3 - 17th IEEE International Conference and Workshops on the Engineering of Computer-Based Systems, ECBS 2010
SP - 311
EP - 315
BT - 17th IEEE International Conference and Workshops on the Engineering of Computer-Based Systems, ECBS 2010
T2 - 17th IEEE International Conference and Workshops on the Engineering of Computer-Based Systems, ECBS 2010
Y2 - 22 March 2010 through 26 March 2010
ER -