Distance aware tag clouds

Abstract

Distance aware tag clouds add visualization of relations between terms to standard tag clouds. In addition to term importance (which is usually depicted through font size) the placement of terms represents the relation between words in the corpus. These relations are modeled as similarities between words and are visualized via the distance between the corresponding tags in the tag cloud. In this paper a modified multi-dimensional scaling (MDS) approach for tag positioning is presented. Applying standard MDS results in unsatisfying and unusable representations due to two problems. The first problem stems from word overlap which is orthogonal to the second problem: excessive empty space. Both of these shortcomings are addressed by introducing methods for overlap removal and empty space reduction. We show that these two modifications only moderately increase the resulting MDS stress value of the new positioning while they remove most of the overlaps and reduce the amount of white space. ©2010 IEEE.