Date of Graduation


Document Type


Degree Name

Bachelor of Science

Degree Level



Computer Science and Computer Engineering


Gauch, Susan

Committee Member/Reader

Deaton, Russell J.

Committee Member/Second Reader

Parkerson, James Patrick


Website personalization systems seek to give users unique, tailored content and experiences on the Internet. A key feature of these systems is a user profile that represents each user in a way that distinguishes them from others. In current personalization systems, the data used to create these profiles is extremely limited, which leads to a host of problems and ineffectual personalization. The main goal of this thesis is to improve these personalization systems by addressing their lack of data and its poor quality, breadth, and depth. This is accomplished by analyzing and classifying the content of each user's Internet browsing activity, rather than just their activity on a single website, to autonomously build persistent, ontology-based user profiles. Furthermore, these profiles are built and stored on a remote server, which allows them to be easily made available to approved websites in the interest of providing the data to enable accurate, relevant, and up-to-date personalization.