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Dynamic Parameter Selection for Community Detection Algorithms (Graph Networks)

Award Information
Agency: Department of Defense
Branch: National Geospatial-Intelligence Agency
Contract: HM047622C0013
Agency Tracking Number: NGA-P1-22-01
Amount: $99,999.44
Phase: Phase I
Program: SBIR
Solicitation Topic Code: NGA212-002
Solicitation Number: 21.2
Solicitation Year: 2021
Award Year: 2022
Award Start Date (Proposal Award Date): 2021-12-20
Award End Date (Contract End Date): 2022-10-03
Small Business Information
9301 Corbin Avenue Suite 2000
Northridge, CA 91324-1111
United States
DUNS: 082191198
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Erford Porter
 (703) 885-8780
Business Contact
 Greg Fetzer
Phone: (303) 651-6756
Research Institution

In the pattern of life problem space, data is often represented via mathematical graphs, in which a variety of algorithms may be employed to conduct semi-autonomous analysis. While successful empirical application of graph-domain algorithms on ABI problems has been achieved, most of these algorithms require a tuning parameter, which is often set heuristically in real-world scenarios. Arete has developed a unique mathematical approach to dramatically reduce the human time required in graph-based intelligence systems based on recent advances in graph homology and topological data analysis (TDA). Our method dynamically and automatically perform parameter selection for graph-based algorithms, is extensible to any machine-readable dataset/algorithm pair, and dramatically improves the computational efficiency of  graph-based algorithms by exploiting their underlying mathematical properties.

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

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