Resolving Independent Perspectives by Providing Learning-Enabled Enhanced Fusion For Elastic Cloud Technologies (RIPPLE-EFFECT)

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-14-P-1095
Agency Tracking Number: N132-135-0650
Amount: $80,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2014
Solicitation Year: 2013
Solicitation Topic Code: N132-135
Solicitation Number: 2013.2
Small Business Information
1235 South Clark Street, Suite 400, Arlington, VA, 22202-
DUNS: 036593457
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Mark Frymire
 Chief Technology Officer
 (703) 414-5139
Business Contact
 Dana Ho
Title: Contracts Manager
Phone: (703) 414-5016
Research Institution
To maintain situational awareness, analysts must sift through and fuse information across multiple documents, data sources, and modalities (text, imagery, and biometrics). The emergence of Big Data has placed an enormous burden on the analyst as the volume of data to examine has increased dramatically while the analyst"s capacity to understand and fuse information remains constant. Additionally, the data remains distributed across geographically separated systems with low-bandwidth connections. The analyst is presented with an incomplete data space from which to produce an intelligence picture. DAC proposes a system called Resolving Independent Perspectives by Providing Learning Enabled Enhance Fusion For Elastic Cloud Technologies (RIPPLE-EFFECT). RIPPLE-EFFECT provides a framework to fuse semantic enhancements from multiple vendors through the use of machine learning algorithms which infer correlations between both the semantic structure and the extracted semantic content. RIPPLE-EFFECT supports scalable cross-document inference over the semantically enhanced data space with dynamically evolving search patterns based on data encountered during the search and the semantic meaning behind the initial query. RIPPLE-EFFECT maintains a consistent data space and intelligence picture across geographically separated systems specialized to the area of interest and time period of interest for each system through lock-free continuous synchronization.

* Information listed above is at the time of submission. *

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