Year of Publication
Season of Publication
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. Ching-Hua Chuan
Dr. Sherif Elfayoumy
Dr. Sherif Elfayoumy
Dr. Mark Tumeo
Web designers are expected to perform the difficult task of adapting a site’s design to fit changing usage trends. Web analytics tools give designers a window into website usage patterns, but they must be analyzed and applied to a website's user interface design manually. A framework for marrying live analytics data with user interface design could allow for interfaces that adapt dynamically to usage patterns, with little or no action from the designers. The goal of this research is to create a framework that utilizes web analytics data to automatically update and enhance web user interfaces. In this research, we present a solution for extracting analytics data via web services from Google Analytics and transforming them into reporting data that will inform user interface improvements. Once data are extracted and summarized, we expose the summarized reports via our own web services in a form that can be used by our client side User Interface (UI) framework. This client side framework will dynamically update the content and navigation on the page to reflect the data mined from the web usage reports. The resulting system will react to changing usage patterns of a website and update the user interface accordingly. We evaluated our framework by assigning navigation tasks to users on the UNF website and measuring the time it took them to complete those tasks, one group with our framework enabled, and one group using the original website. We found that the group that used the modified version of the site with our framework enabled was able to navigate the site more quickly and effectively.
Carle, William R. II, "Active Analytics: Adapting Web Pages Automatically Based on Analytics Data" (2016). UNF Graduate Theses and Dissertations. 629.