RMAP: a system for visualizing data in multidimensional relevance space
We describe a prototype system, RMAP, for visualizing information distribution in a multidimensional relevance space. The information displayed consists 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 visualization of that information, where the exact relevance measures of the objects are 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 engines, automatically categorizes and clusters the information and allow the user to visualize.
relevance map world wide web user information data visualization search engines