Challenges in Machine Generation of Analytic Products from Multi-Source Data
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A01=and Medicine
A01=Division on Engineering and Physical Sciences
A01=Engineering
A01=Intelligence Community Studies Board
A01=National Academies of Sciences
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and Medicine
Author_and Medicine
Author_Division on Engineering and Physical Sciences
Author_Engineering
Author_Intelligence Community Studies Board
Author_National Academies of Sciences
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B01=Linda Casola
Category1=Non-Fiction
Category=PB
COP=United States
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Engineering
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Language_English
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Price_€50 to €100
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Product details
- ISBN 9780309465731
- Dimensions: 216 x 279mm
- Publication Date: 03 Nov 2017
- Publisher: National Academies Press
- Publication City/Country: US
- Product Form: Paperback
- Language: English
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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.
