Similarity Measures for Human Networks

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-09-M-0436
Agency Tracking Number: N092-149-0729
Amount: $70,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2010
Solicitation Year: 2009
Solicitation Topic Code: N092-149
Solicitation Number: 2009.2
Small Business Information
Aptima, Inc.
12 Gill Street, Suite 1400, Woburn, MA, 01801
DUNS: 967259946
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Jean MacMillan
 Chief Scientist
 (781) 496-2412
 macmillj@aptima.com
Business Contact
 Margaret Clancy
Title: Chief Financial Officer
Phone: (781) 496-2415
Email: clancy@aptima.com
Research Institution
N/A
Abstract
The search for entities of interest (either individuals or groups) in large behavioral datasets has emerged as a key need for irregular warfare, counter-insurgency, and counter-terrorism. This search requires measures of similarity between networks, and the combination of diverse multi-dimensional measures into a single meaningful scalar measure of similarity. To address this challenge, Aptima has teamed with two leaders in the field of human network research: Dr. Kathleen Carley from Carnegie Mellon University and Dr. Alex (Sandy) Pentland from the MIT Media Lab. Dr. Carley brings a meta-matrix framework developed for computational organizational modeling to the team. Dr. Pentland brings his sociometric network similarity measurement work, which introduces similarity measures based on data from new types of wearable sensors. Aptima’s work on human network similarity from a system engineering and network science perspective forms a third component and serves as a bridge. Testing of measures in Phase I will use a hybrid real-synthetic dataset. A hypothetical test case will represent a “person or group of interest” and the Aptima team will calculate measures of similarity between the entities in the dataset and the synthetic target of interest, analyzing the effects of varying levels of uncertainty on the similarity measure.

* information listed above is at the time of submission.

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