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ISVG Featured in Press Release from Partner iXreveal

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The following press release details ISVG’s use of the iXreveal product line with ISVG data holdings to identify and quickly narrow incidents and groups related to the Time Square Bombing incident.

For immediate Release

IXREVEAL UNRAVELS CRITICAL PATTERNS IN TIMES SQUARE BOMBING

(Washington D.C. August 23, 2010) Software from IxReveal has successfully matched methods used in the Times Square bombing to specific techniques used by radical Islamists in previous attacks in other parts of the world.

The Institute for the Study of Violent Groups (ISVG) associated with the University of New Haven, West Haven, CT,  immediately began the analysis after the incident using publicly released information combined with its own extensive relational database containing over 180,000 unique events, most of them terror related. It also included its extensive collection of unstructured textual reports.  ISVG used the IxReveal platform because of its ability to access and analyze multiple filed types, both structured and unstructured quickly and efficiently.  The analysis finds links and relationships that elude other analytical tools.

The first details of the attempted bombing to be released were a small number of bomb components used in the attack. With this information, ISVG employed IxReveal to find only incidents in which propane or fertilizer was used in conjunction with gasoline. This yielded 99 such incidents.

Narrowing the pool of potential matched incidents was a priority.  The additional information available was that the bomb was in a vehicle. The analysts then used the software’s ability to allow the analyst to easily perform an analysis using multiple titles or names for a category ( in this case, vehicle) in order to further analyze the 99 events identified that had the indicated bomb components to events which included a vehicle used in an attack.  Combining vehicle names such as “truck”, “van”, “car”, “SUV”, “make or model of car, “etc.  would accurately identify any incident that met both criteria. The results of this analysis produced only 40 results.

With the most relevant incidents now identified, the ISVG specialists further narrowed the possibilities to six incidents through visual inspection.  Of these six, two contained information very closely related to the Times Square Bombing. The first was the attack on the U.S. Embassy in Syria (September 2006.)  The second was to the attempted bombings in London (June 2007.)  Both of these incidents had been tied to Al-Qaeda or Al-Qaeda related groups.

The results that IxReveal allowed ISVG to quickly find demonstrated that two of the six events identified were related in some way to radical Islamists. Josh  Hill of ISVG notes, “ Using IxReveal, we were quickly able to match events to demonstrate there was good evidence that the Times Square bomber had ties to radical Islam and may have received training from, or similar to, the bombers the Syria and London incidents. IxReveal quickly enabled us to produce highly accurate analysis from a large set of disparate data. It gave us the flexibility to quickly identify other similar incidents and fast analysis of those incidents. The result was insight from the information and immediate dissemination to partners.”

IxReveal, Inc. is a leading text analytics software company that revolutionizes analysis of data, both structured and unstructured. The company’s solution-based products are unique in their capacity to transform large volumes of unstructured and structured data into actionable intelligence.  IxReveal’s award winning product lines, uReveal and uReka!, allow researchers to collaboratively share concepts and  findings.  Clients include leading multinational corporations, financial institutions, law enforcement agencies, universities, health organizations, and major federal agencies with data-intensive mandates.  For more information about IxReveal, visit www.IxReveal.com.

Contact:

Beth McCague

IxReveal, Inc.

904 421 7385

Beth.mccague@ixreveal.com

mgray@isvg.org

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