College of Computing, Engineering & Construction
Master of Science in Computer and Information Sciences (MS)
NACO controlled Corporate Body
University of North Florida. School of Computing
Dr. Karthikeyan Umapathy
Dr. Xudong Liu
Dr. Sandeep Reddivari
Dr. Sherif Elfayoumy
Dr. William F. Klostermeyer
Front-end developers are tasked with keeping websites up-to-date while optimizing user experiences and interactions. Tools and systems have been developed to give these individuals granular analytic insight into who, with what, and how users are interacting with their sites. These systems maintain a historical record of user interactions that can be leveraged for design decisions. Developing a framework to aggregate those historical usage records and using it to anticipate user interactions on a webpage could automate the task of optimizing web pages. In this research a system called Active Analytics was created that takes Google Analytics historical usage data and provides a dynamic front-end system for automatically updating web page navigational elements. The previous year’s data is extracted from Google Analytics and transformed into a summarization of top navigation steps. Once stored, a responsive front-end system selects from this data a timespan of three weeks from the previous year: current, previous and next. The most frequently reached pages, or their parent pages, will have their navigational UI elements highlighted on a top-level or landing page to attempt to reduce the effort to reach those pages. The Active Analytics framework was evaluated by eliciting volunteers by randomly assigning two versions of a site, one with the framework, one without. It was found that users of the framework-enabled site were able to navigate a site more easily than the original.
Koza, Jacob, "Active Analytics: Suggesting Navigational Links to Users Based on Temporal Analytics Data" (2019). UNF Graduate Theses and Dissertations. 892.