Faceted Browsing over Large Databases of Text-Annotated Objects

We demonstrate a fully working system for multifaceted browsing over large collections of text-annotated data, such as annotated images, that are stored in relational databases.  Typically, such databases can be browsed across multiple facets (by topic, genre, location, and so on) and previous user studies showed that multifaceted interfaces improve substantially the ability of users to identify items of interest in the database.  We demonstrate a scalable system that automatically generates multifaceted browsing hierarchies on top of a relational database that stores the underlying text-annotated objects.  Our system supports a wide range of ranking alternatives for selecting and displaying the best facets and the best portions of the generated hierarchies, to facilitate browsing.  We combine our ranking schemes with Rapid Serial Visual Presentation (RSVP), an advanced visualization technique, which further enhances the browsing experience and demonstrate how to use prefetching techniques to overcome the latency issues that are inherent when browsing the contents of a relational database using multifaceted interfaces.