Date of Award
Daniel Felix Ritchie School of Engineering and Computer Science, Computer Science
Young Jin Lee
Privacy policies notify Internet users about the privacy practices of websites, mobile apps, and other products and services. However, users rarely read them and struggle to understand their contents. Also, the entities that provide these policies are sometimes unmotivated to make them comprehensible. Due to the complicated nature of these documents, it gets even harder for users to understand and take note of any changes of interest or concern when these policies are changed or revised.
The research work not only shows the potential of machine learning and natural language processing as an important tool for privacy engineering but also introduces various techniques that can be utilized for any natural language document.
Copyright is held by the author. User is responsible for all copyright compliance.
Received from ProQuest
Adhikari, Andrick, "Automated Change Detection in Privacy Policies" (2020). Electronic Theses and Dissertations. 1706.
Computer science, Artificial intelligence