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Rapid Response Data Science for COVID-19

Bandlow, Alisa B.; Bauer, Travis L.; Crossno, Patricia J.; Garcia, Rudy J.; Astuto Gribble, Lisa A.; Hernandez, Patricia M.; Martin, Shawn; McClain, Jonathan T.; Patrizi, Laura P.

This report describes the results of a seven day effort to assist subject matter experts address a problem related to COVID-19. In the course of this effort, we analyzed the 29K documents provided as part of the White House's call to action. This involved applying a variety of natural language processing techniques and compression-based analytics in combination with visualization techniques and assessment with subject matter experts to pursue answers to a specific question. In this paper, we will describe the algorithms, the software, the study performed, and availability of the software developed during the effort.

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Data privacy and security considerations for personal assistantsfor learning (PAL)

International Conference on Intelligent User Interfaces, Proceedings IUI

Raybourn, Elaine M.; Fabian, Nathan D.; Davis, Warren L.; Parks, Raymond C.; McClain, Jonathan T.; Trumbo, Derek T.; Regan, Damon; Durlach, Paula J.

A hypothetical scenario is utilized to explore privacy and security considerations for intelligent systems, such as a Personal Assistant for Learning (PAL). Two categories of potential concerns are addressed: factors facilitated by user models, and factors facilitated by systems. Among the strategies presented for risk mitigation is a call for ongoing, iterative dialog among privacy, security, and personalization researchers during all stages of development, testing, and deployment.

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10 Results
10 Results