Master of Science in Computer Engineering (MSCE), Wright State University, 2018, Computer Engineering

When presented with many search results, finding information or patterns within the data poses a challenge. This thesis presents the design, implementation and evaluation of a visualization enabling users to browse through voluminous information and comprehend the data. Implemented with the JavaScript library Data Driven Documents (D3), the visualization represents the search as clusters of similar documents grouped into bubbles with the contents depicted as word-clouds. Highly interactive features such as touch gestures and intuitive menu actions allow for expeditious exploration of the search results. Other features include drag-and-drop functionality for articles among bubbles, merging nodes, and refining the search by selecting specific terms or articles to receive more similar results. A user study consisting of a survey questionnaire and user tracking data demonstrated that in comparison to a standard text-browser for viewing search results, the visualization performs commensurate or better on most metrics.

Committee: Thomas Wischgoll Ph.D. (Advisor); Michael Raymer Ph.D. (Committee Member); John Gallagher Ph.D. (Committee Member) Subjects: Computer Engineering; Computer Science