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The Intelligence Community Studies Board of the National Academies of Sciences, Engineering, and Medicine convened a workshop on August 9-10, 2017 to examine challenges in machine generation of analytic products from multi-source data. Workshop speakers and participants discussed research challenges related to machine-based methods for generating analytic products and for automating the evaluation of these products, with special attention to learning from small data, using multi-source data, adversarial learning, and understanding the human-machine relationship. This publication summarizes the presentations and discussions from the workshop.

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Suggested Citation

National Academies of Sciences, Engineering, and Medicine. 2017. Challenges in Machine Generation of Analytic Products from Multi-Source Data: Proceedings of a Workshop. Washington, DC: The National Academies Press. https://doi.org/10.17226/24900.

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Publication Info

70 pages |  8.5 x 11 | 

ISBNs: 
  • Paperback:  978-0-309-46573-1
  • Ebook:  978-0-309-46576-2
DOI: https://doi.org/10.17226/24900

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