SBIR-STTR Award

AutoNet: Rapid and Automatic Social Network Creation from Disparate Data Sources
Award last edited on: 1/14/2013

Sponsored Program
SBIR
Awarding Agency
DOD : OSD
Total Award Amount
$99,984
Award Phase
1
Solicitation Topic Code
OSD10-HS6
Principal Investigator
Sofus Attila Macskassy

Company Information

Fetch Technologies (AKA: Connotate Solutions~Dynamic Domain )

841 Apollo Street Suite 400
El Segundo, CA 90245
   (310) 414-9849
   info@fetch.com
   www.fetch.com
Location: Single
Congr. District: 33
County: Los Angeles

Phase I

Contract Number: ----------
Start Date: ----    Completed: ----
Phase I year
2011
Phase I Amount
$99,984
Here we propose to develop technologies which automatically generates a social network by analyzing incoming data feeds, integrating the data around the entities and (semi-)automatically generate the relations between the entities. Because the saliency of a network is critical for important intelligence products where people are on the line, we envision that the creation of a social network be done with a human-in-the-loop, where the computer does the hard analytic lifting and the human directs the kinds of relations to look for and verifies that the relations are indeed correct before sending the network on for network analysis. We propose to investigate two key technologies which directly relate to this SBIR topic: (1) automatic extraction of relations from multiple disparate information feeds, and (2) workflows for rapid definition, creation, modification and extraction of relations. Both of these are critical pieces which are needed in order to speed up the creation of social networks for network analytics in intelligence products.

Keywords:
Information Extraction, Relation Extraction, Entity Resolution, Social Network Creation, Text Analysis

Phase II

Contract Number: ----------
Start Date: ----    Completed: ----
Phase II year
----
Phase II Amount
----