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DARPA system to blend AI, machine learning to understand mountain of text

DARPA wants automated system that includes technology from artificial intelligence, computational linguistics, machine learning, natural-language fields

By Layer 8 on Fri, 05/04/12 - 11:47am.

darpa deftThe Defense Advanced Research Projects Agency (DARPA) will next this month detail the union of advanced technologies from artificial intelligence, computational linguistics, machine learning, natural-language fields it hopes to bring together to build an automated system that will let analysts and others better grasp meanings from large volumes of text documents.

From DARPA: "Automated, deep natural-language understanding technology may hold a solution for more efficiently processing text information. When processed at its most basic level without ingrained cultural filters, language offers the key to understanding connections in text that might not be readily apparent to humans. Sophisticated artificial intelligence of this nature has the potential to enable defense analysts to efficiently investigate orders of magnitude more documents so they can discover implicitly expressed, actionable information contained within them."

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Technology developed within the Deep Exploration and Filtering of Text (DEFT)  program is expected to provide the capability to identify and interpret both explicit and implicit information from highly ambiguous and vague narrative text, and integrate individual facts into large domain models for assessment, planning and prediction, DARPA stated.

"Overwhelmed by deadlines and the sheer volume of available foreign intelligence, analysts may miss crucial links, especially when meaning is deliberately concealed or otherwise obfuscated," said Bonnie Dorr, DARPA program manager for DEFT. "DEFT is attempting to create technology to make reliable inferences based on basic text. We want the ability to mitigate ambiguity in text by stripping away filters that can cloud meaning and by rejecting false information. To be successful, the technology needs to look beyond what is explicitly expressed in text to infer what is actually meant."

Dorr added that much of the basic research needed for DEFT has been accomplished, but now has to be scaled, applied and integrated through the development of new technology.  DAPRA will hold a proposers' day in Arlington, VA on May 16 to detail DEFT.

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DARPA has a number of other programs that are looking to make sense of large volumes of data including: