This decommissioned ERA site remains active temporarily to support our final migration steps to https://ualberta.scholaris.ca, ERA's new home. All new collections and items, including Spring 2025 theses, are at that site. For assistance, please contact erahelp@ualberta.ca.
Search
Skip to Search Results
Filter
Subject / Keyword
- 1 latent dirichlet allocation
- 1NSA
- 1data surveillance
- 1machine learning
- 1national security agency
- 1topic modeling
Supervisors
Author / Creator / Contributor
Year
Collections
Languages
Item type
Departments
-
Using Machine Learning to Understand the National Security Agency’s Data Surveillance Trends
DownloadFall 2021
For over six decades, the public has remained ignorant about the National Security Agency (NSA) and its activities and has been shielded from the agency’s invasive and unlawful projects. While the NSA’s activities have proven valuable to the United States and its allies, it sometimes undertakes...
1 - 1 of 1