True Colors: Persona/Human Network Similarity Quantification Software

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$69,920.00
Award Year:
2010
Program:
SBIR
Phase:
Phase I
Contract:
N00014-09-M-0438
Agency Tracking Number:
N092-149-0166
Solicitation Year:
2009
Solicitation Topic Code:
N092-149
Solicitation Number:
2009.2
Small Business Information
Michigan Aerospace Corporation
1777 Highland Drive, Suite B, Ann Arbor, MI, 48108
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
969868298
Principal Investigator:
John Trenkle
Senior Scientist
(734) 975-8777
jtrenkle@michaero.com
Business Contact:
Peter Tchoryk
Chief Executive Officer
(734) 975-8777
ptchoryk@michaero.com
Research Institution:
n/a
Abstract
In response to Navy SBIR topic N092-149, “Similarity Measures for Persona/Human Networks”, Michigan Aerospace Corporation (MAC) proposes the True Colors system (TC): an application that utilizes a unique means of assessing, quantifying and understanding the relationship between N-dimensional vectors which represent signatures capturing the behavior and activities of individuals or groups. Unlike popular distance and similarity metrics, the TC technique for assessing similarity does not require normalization, works with mixed numeric and categorical fields, gracefully handles missing entries, and can function appropriately in the case of imbalanced or sparsely populated records. TC is based on several years of research conducted by MAC staff in conjunction with government and industry partners in applying Ensembles of Decision Trees (EDTs) to challenging problems in Data Mining and Pattern Recognition including clustering. Advantages to this approach, include confidence estimations and relative feature importance assessment. MAC will use anonymized human interactions harvested from the well-known Slashdot forums as a testbed to demonstrate TC similarity principles. Slashdot forums supply a wealth of information about authors, users, topics, and cliques of like-minded members. The ability to assess similarity between items of varied composition has key applications in business, biology, social network analysis and many other fields.

* information listed above is at the time of submission.

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