15 May 2015 Towards an automated intelligence product generation capability
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Abstract
Creating intelligence information products is a time consuming and difficult process for analysts faced with identifying key pieces of information relevant to a complex set of information requirements. Complicating matters, these key pieces of information exist in multiple modalities scattered across data stores, buried in huge volumes of data. This results in the current predicament analysts find themselves; information retrieval and management consumes huge amounts of time that could be better spent performing analysis. The persistent growth in data accumulation rates will only increase the amount of time spent on these tasks without a significant advance in automated solutions for information product generation. We present a product generation tool, Automated PrOduct Generation and Enrichment (APOGEE), which aims to automate the information product creation process in order to shift the bulk of the analysts’ effort from data discovery and management to analysis. APOGEE discovers relevant text, imagery, video, and audio for inclusion in information products using semantic and statistical models of unstructured content. APOGEEs mixed-initiative interface, supported by highly responsive backend mechanisms, allows analysts to dynamically control the product generation process ensuring a maximally relevant result. The combination of these capabilities results in significant reductions in the time it takes analysts to produce information products while helping to increase the overall coverage. Through evaluation with a domain expert, APOGEE has been shown the potential to cut down the time for product generation by 20x. The result is a flexible end-to-end system that can be rapidly deployed in new operational settings.
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Alison M. Smith, Alison M. Smith, Timothy W. Hawes, Timothy W. Hawes, James J. Nolan, James J. Nolan, } "Towards an automated intelligence product generation capability", Proc. SPIE 9499, Next-Generation Analyst III, 94990R (15 May 2015); doi: 10.1117/12.2184172; https://doi.org/10.1117/12.2184172
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