Online Archive of University of Virginia Scholarship
Integration of New Active Learning Algorithms to Plaster: A Framework for Heterogeneous Metadata Normalization Methods; Analyzing Ethical and Social Responsibility for the Present and Future of Smart Building Technology368 views
Author
Yoon, David, School of Engineering and Applied Science, University of Virginia
Advisors
JACQUES, RICHARD, EN-Engineering and Society, University of Virginia
Wang, Hongning, EN-Comp Science Dept, University of Virginia
Abstract
Discusses the implementations of various active learning algorithms into Plaster, a framework for heterogeneous metadata normalization methods. Additionally, this portfolio analyzes the ethical and social environment for the present and future of smart building technology.
Degree
BS (Bachelor of Science)
Keywords
Smart Building ; Software ; Users and Non-Users; Active Learning
School of Engineering and Applied Sciences
Bachelor of Science in Computer Science
Technical Advisor: Hongning Wang
STS Advisor: Richard Jacques
Technical Team Members: None
Language
English
Rights
All rights reserved (no additional license for public reuse)
Yoon, David. Integration of New Active Learning Algorithms to Plaster: A Framework for Heterogeneous Metadata Normalization Methods; Analyzing Ethical and Social Responsibility for the Present and Future of Smart Building Technology. University of Virginia, School of Engineering and Applied Science, BS (Bachelor of Science), 2020-12-13, https://doi.org/10.18130/v3-4gnh-sn19.
