Rosso Tiziano: a system for user-centered exploration and discovery in large information bases

Retrieval in image information bases has been traditionally addressed by two different and unreconciled approaches: the first one uses normal query methods on metadata or on a textual description of each item. The second one works on primitive multimedia features (such as color, texture, etc.) and tries to find items that are similar to a specific selected item. Neither of these approaches supports the most common end-user task: the exploration of an information base in order to find the “right” items. This paper describes a prototype system based on dynamic taxonomies, a model for the intelligent exploration of heterogeneous information bases, and shows how the system implements a new access paradigm supporting guided exploration and discovery and the seamless integration of access through metadata with methods based on primitive multimedia features. Example interactions are discussed, as well as the major implications of this approach.