RMAP: a system for visualizing data in multidimensional relevance space

Jackie Assa, Daniel Cohen-Or, Tova Milo

Abstract: 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.