Data Visualization and Analytics
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A novel hybrid visualization model for representing hierarchically clustered networks, which also supports directed and weighted edges, is introduced and an extensive experimental comparison of these algorithmic approaches is presented to highlight the trade‐offs between efficiency and effectiveness.
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Abstract We introduce C lusterix , a novel hybrid visualization model for representing hierarchically clustered networks, which also supports directed and weighted edges. C lusterix offers an integrated view of both the network and its full cluster hierarchy by compactly visualizing the cluster inclusion tree enriched with links of the network. This is achieved through matrix‐based representations at various hierarchy levels, combined with a node‐link style linear layout at the leaf level. To support layout computation based on C lusterix , we propose two algorithmic approaches: an exact Integer Linear Program and a fast heuristic, both aimed at minimizing edge crossings. We present an extensive experimental comparison of these algorithmic approaches to highlight the trade‐offs between efficiency and effectiveness. Moreover, as a proof of concept for our model, we developed an interactive visualization system based on C lusterix and evaluated its performance through case studies and qualitative feedback from experts in different application domains.
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@article{Binucci2026usterix,
title = {CL usterix : A Hybrid Visualization Model for Hierarchically Clustered Networks},
author = {Carla Binucci and Annika Bonerath and Walter Didimo and Henry Förster and Seok-Hee Hong and Maria Eleni Pavlidi and Alessandra Tappini},
journal = {Computer Graphics Forum},
year = {2026},
doi = {10.1111/cgf.70469},
url = {https://doi.org/10.1111/cgf.70469}
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