RMAP: a system for visualizing data in multidimensional relevance space

We describe a prototype system, RMAP, for visualizing information distribut ion in a multidimensional relevance space. The information displayed consis ts of many objects, a set of features likely to interest the user, and some function that measures the relevance level of every object to the various features. The goal is to provide the user with a comprehensible visualizati on of that information, where the exact relevance measures of the objects a re not significant. We flatten the multidimensionality of the feature space into a 2D relevance map, capturing the inter-relations among the features. The prototype, extract information from the World Wide Web from query engi nes, automatically categorizes and clusters the information and allow the u ser to visualize.