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Skip to Search Results- 7Big data
- 2Machine learning
- 2Matrix factorization
- 1Aboriginal identification
- 1Artificial intelligence
- 1Cancer screening
- 1Chen, Haolan
- 1E, Hanyu
- 1Gerlitz, Laura M
- 1Hossain, Samina
- 1Mayan, Maria (Supervisor)
- 1Montague, John J
- 6Graduate and Postdoctoral Studies (GPS), Faculty of
- 6Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 1University of Alberta Library
- 1University of Alberta Library/Libraries Staff Presentations
- 1Communications and Technology Graduate Program
- 1Communications and Technology Graduate Program/Capping Projects (Communications and Technology)
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Fall 2019
The traditional electric grid based on centralized generation plants and unidirectional transmission and distribution systems is transitioning to a smart grid that is decentralized and multidirectional with high integration of information and communication technologies. With the rapid development...
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2017-10-01
Gerlitz, Laura M, Vanderjagt, Leah
Over the last several years, many academic libraries have engaged in institution-wide outreach efforts promoting the value of research data management and the importance of data archiving and sharing. A happy result of this work is that PIs leading research projects that are concluding are now...
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Fall 2022
Fuzzy models, especially fuzzy rule-based models, have received substantial attention as an important pursuit in the design and analysis of intelligent systems. In rule-based architectures, functional (Takagi-Sugeno) fuzzy rule-based models have been studied intensively resulting in a wealth of...
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Public Health Applications Using Big Data and Machine Learning Methods: Name- and Location-based Aboriginal Ethnicity Classification and Sentiment Analysis of Breast Cancer Screening in the United States Using Twitter
DownloadFall 2017
Applications using big data and machine learning techniques are transforming how people live in the 21st century, however they are generally underutilized in public health compared to other domains. We proposed and conducted two independent studies to investigate how big data and machine learning...
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Separating-Plane Factorization Models: Scalable Recommendation from One-class Implicit Feedback
DownloadFall 2016
We study the large-scale video recommendation problem based on user viewing logs instead of explicit ratings. As viewing records are implicitly positive samples, existing matrix factorization methods fail to generate discriminative recommendations based on such one-class data. We propose a...
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Fall 2016
Big data applications demand and consequently lead to developments of diverse scalable data management systems, ranging from NoSQL systems to the emerging NewSQL systems. In order to serve thousands of applications and their huge amounts of data, data management systems must be capable of...
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Spring 2016
How can the principles and concepts applied by visual communication designers be used to assist in exploring and understanding the massive, complex volumes of data now available to Digital Humanities researchers? One method we might employ to help us more easily comprehend the implications of...