Data-Driven Authorship Feature Extraction and Comparative Analysis using Machine Learning

Award Information
Agency: Department of Defense
Branch: Army
Contract: W56KGU-18-C-0045
Agency Tracking Number: A181-054-1393
Amount: $100,000.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: A18-054
Solicitation Number: 2018.1
Timeline
Solicitation Year: 2018
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-07-19
Award End Date (Contract End Date): 2019-01-18
Small Business Information
215 Parkway North, Waterford, CT, 06385
DUNS: 077317766
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Mr. Stephen Dorton
 (860) 326-3646
 sdorton@sonalysts.com
Business Contact
 Ms. Donna LaBranche
Phone: (860) 326-3734
Email: dlabranche@sonalysts.com
Research Institution
N/A
Abstract
Sonalysts will develop the Authorship and Intent Recognition Environment (AIRE), an adaptive platform that provides automated and semi-automated analyses for Information Operations (IO) based on textual information and other data sources. AIRE will use a variety of analytical techniques, including Machine Learning (ML) and Artificial Intelligence (AI) methods, as well more explainable methods such as Qualitative Comparative Analysis (QCA). Analysts will interact with intuitive interfaces in a visual environment built around their workflows. AIRE will leverage AI/ML techniques to find trends and connect the dots among data, and then allow more explainable statistical methods to be run on data to provide more explainability to the analyst than using black box methods alone. These methods will be combined with the use of deep linguistic features, such as semantic information and other relevant metadata, to fuse authorship detection and intent recognition methods, rather than treating them as separate routines. This combination of analytical techniques in an intuitive interface will make AIRE a significant innovation and a valuable tool to several end users.

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

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