Information selection in intelligence processing

In many intelligence agencies, the processing of data into usable information ready for analysis poses a significant bottleneck. Typically, much more data is available than what can be processed in the limited time available for processing. We formulate the problem faced by an intelligence collection unit, when processing incoming raw information for delivery to intelligence analysts, as an exploration-exploitation problem: the processor has to choose between exploring for new sources of relevant information and exploiting known sources. To address the exploration-exploitation problem, we develop a mathematical model of the processor's knowledge and examine algorithms that allow the processor to maximize the discovery of relevant data given a time limit. We derive insights on the performance of different algorithms using a simulated case study.

Department dc:contributor.department

Operations Research

Grantor dc:publisher

Monterey, California. Naval Postgraduate School

Year dc:date.issued

2011

Author dc:creator

• Nevo, Yuval.

Advisors dc:contributor.advisor

• Kress, Moshe
• Dimitrov, Nedialko B.

Statement dc:rights

• This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.

Handle dc:identifier.uri

https://hdl.handle.net/10945/10660

OAI identifier oai:identifier

oai:calhoun.nps.edu:10945/10660