Cluster-based visualization of concept associations

One of the steps in the knowledge domain visualization process is the display of the low-dimensional space in which the items under analysis are positioned. In this paper we investigate the visualization of concept associations by means of concept clustering and edge bundling, two techniques that help alleviate the cluttering caused by concept labels and edges. Hierarchical clustering is used for the identification of the different domain categories (i.e., clusters). The edges between pairs of concepts belonging to two clusters are aggregated in a single edge connecting the clusters' centers. The proposed approach enables us to discover the hierarchical structure of our knowledge domain and analyze the strength between the different domain categories.

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