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.
Theses and Dissertations
This collection contains theses and dissertations of graduate students of the University of Alberta. The collection contains a very large number of theses electronically available that were granted from 1947 to 2009, 90% of theses granted from 2009-2014, and 100% of theses granted from April 2014 to the present (as long as the theses are not under temporary embargo by agreement with the Faculty of Graduate and Postdoctoral Studies). IMPORTANT NOTE: To conduct a comprehensive search of all UofA theses granted and in University of Alberta Libraries collections, search the library catalogue at www.library.ualberta.ca - you may search by Author, Title, Keyword, or search by Department.
To retrieve all theses and dissertations associated with a specific department from the library catalogue, choose 'Advanced' and keyword search "university of alberta dept of english" OR "university of alberta department of english" (for example). Past graduates who wish to have their thesis or dissertation added to this collection can contact us at erahelp@ualberta.ca.
Items in this Collection
- 42machine learning
- 7reinforcement learning
- 6artificial intelligence
- 4deep learning
- 2anomaly detection
- 2clustering
- 1Afrin, Afia
- 1Badamdorj, Taivanbat
- 1Balasooriya Arachchilage, Chathuranga S J
- 1Bennett, Brendan
- 1Benoit, James RA
- 1Carlos Manuel Martínez
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Using Machine Learning and Keyword Analysis to Analyze Incident Reports and Reduce Risk in Oil Sands Operations
DownloadSpring 2020
Many companies maintain large databases of incident reports. Incidents that have severe consequences are analyzed in detail to prevent recurrence, while minor incidents are typically stored without any further evaluation. Especially with common incidents and those with lesser consequences,...
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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...