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Embedded Space Analytics

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-16-P-1038
Agency Tracking Number: N16A-020-0228
Amount: $80,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N16A-T020
Solicitation Number: 2016.0
Timeline
Solicitation Year: 2016
Award Year: 2016
Award Start Date (Proposal Award Date): 2016-07-11
Award End Date (Contract End Date): 2017-05-10
Small Business Information
320 Whittington PKWY
Louisville, KY 40222
United States
DUNS: 877380530
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: Yes
Principal Investigator
 Bin Xie
 (502) 371-0907
 Bin.Xie@InfoBeyondtech.com
Business Contact
 Debbie Qiu
Phone: (502) 371-0908
Email: Debbie.qiu@InfoBeyonds.com
Research Institution
 University of Louisville
 Lauren Goralski
 
300 East Market Street, Suite 300 \N
Louisville, KY 40202-1959
United States

 (502) 852-2597
 Nonprofit college or university
Abstract

Navy needs a real-time graph embedding tool for analyzing huge graphs (millions of nodes and billions of edges) from diverse sources. However, current approaches cannot provide dynamic and scalable graph analytics to show the military value of tactical data. In this project, InfoBeyond advocates EStreaming (Embedding & Streaming) for scalable and efficient graph streaming. EStreaming promotes big data streaming technology where unsupervised and semi-supervised machine learning algorithms can be conducted over the streaming platform. It can split a huge graph into small subgraphs such that distributed graph embedding can be conducted in parallel among a set of processors. Meanwhile, the graph embedding can be effectively merged and visualized. Considering the diversity of Navy applications, EStreaming is an open platform that can implement many graph embedding algorithms such as IsoMap, LLE, Laplacian eigenmap, and graph factorizations. We have demonstrated the implementation of Distributed LINE (DLINE) and Distributed MVE (DMVE). Compared to other algorithms, classification of DLINE can be conducted from the internal relations and the similarity among the persons in the solider, enemy, and other social networks. Differently, DMVE can be used for analyzing spatial - temporal data such as for ISR sensor networks, e.g., Navy ISR geographic traffic monitoring.

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

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