Evaluation and evolution of a browse and search interface: relation browser

We present in this paper the design and an evaluation of a novel interface called the Relation Browser++ (RB++) for searching and browsing large information collections. RB++ provides visualized category overviews of an information space and allows dynamic filtering and exploration of the result set by tightly coupling the browsing and searching functions. A user study was conducted to compare the effectiveness, efficiency and user satisfaction of completing various types of searching and browsing using the RB++ interface and a traditional form-fillin interface for a video library. An exploration set of tasks was also included to examine the effectiveness of and user satisfaction with the RB++ when applied to a large federal statistics website. The comparison study strongly supported that RB++ was more effective, efficient, and satisfying for completing data exploration tasks. Based on the results, efforts to automatically populate the underlying database using machine learning techniques are underway. Preliminary implementations for two large-scale federal statistical websites have been installed on government servers for internal evaluation.

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