Need for metrics in visual information analysis

Abstract

This paper explores several methods for visualizing the thematic content of large document collections. As opposed to traditional query-driven document retrieval, these methods are used for exploring and gaining insight into document collections. For our experiments, we used 12,000 medical abstracts. The SPIRET system was used to create the mathematical signal from text and to project the documents into a universe of 'docustars' and as a thematic contour map based on thematic proximity. A self-organizing map is used to project the documents onto a 'Tree' fractal. A topic-based approach is used to align documents between concepts in the 'Cosmic Tumbleweed' projection. In the 32-D Hypercube, documents are organized by cascading theme strengths. An argument is made for a new type of metric that would facilitate comparisons among the many methods for visualizing or browsing document collections. An initial organization is proposed for some of the relevant research that metrics for information visualization can draw upon.