Situational Awareness as a Man-Machine Map Reduce Job

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-13-P-1177
Agency Tracking Number: N13A-024-0078
Amount: $79,999.00
Phase: Phase I
Program: STTR
Awards Year: 2013
Solicitation Year: 2013
Solicitation Topic Code: N13A-T024
Solicitation Number: 2013.A
Small Business Information
1235 South Clark Street, Suite 400, Arlington, VA, -
DUNS: 036593457
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Jonathan Clausen
 Senior Engineer
 (703) 414-5020
Business Contact
 Dana Ho
Title: Contracts Manager
Phone: (703) 414-5016
Research Institution
 University of Maryland
 Katie McKeon
 Lee Building
College Park, MD, 20742-5141
 (301) 405-6274
 Nonprofit college or university
This effort is focused on the development of a system called Situational Awareness via Mixed-initiative Universal Recognition, Analysis, and Inference (SAMURAI). SAMURAI will provide a single cloud-enabled end-to-end workflow covering the full range of data analysis from data ingest to situational assessment and decision support. As part of this workflow SAMURAI will provide the ability for automated processing to provide rapid extraction of knowledge while allowing manual corrections and additions at multiple levels. These manual changes will then be utilized to improve the underlying statistical models utilized within the automated processes. The SAMURAI system will also provide a behavior/intent prediction capability that has been demonstrated to operate on millions of entities and billions of relationships. Moreover, the prediction algorithms will have the ability to be updated according to analyst feedback and use analyst-provided information not present in the raw data. The overall efficiency and accuracy of a large scale, mixed initiative analytical system will be heavily affected by when and how users provide feedback to the algorithms, the system incorporates this feedback, and users interact with each other. SAMURAI identifies when such interactions have the greatest benefit, and advises the user accordingly.

* information listed above is at the time of submission.

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