From user query to user model and back: Adaptive relevance-based visualization for information foraging

Adaptive information filtering is a promising tool for both casual Web news readers and professional intelligence analysts. Adaptive filtering augments the traditional query- or profile-based rankings provided by search engines. An interesting research challenge in this context is to offer users more control over the rankings by letting them mediate between the two extremes - query- and profile-based rankings. To address this challenge, we developed an adaptive relevance-based visual exploration tool based on the VIBE (Visual Information Browsing Environment) visualization approach, which was previously developed at our School. This paper presents the rationale and functionality of this visual exploration tool and reports the results of its preliminary evaluation.