Aggregating Hypergraphs by Node Attributes
Date:
Recommended citation: Trye, D., Apperley, M., & Bainbridge, D. (2022). Aggregating hypergraphs by node attributes. In Angelini, P., & von Hanxleden, R. (Eds.), Graph Drawing and Network Visualization: 30th International Symposium, GD 2022, Tokyo, Japan, September 13–16, 2022, Revised Selected Papers (Vol. 13764, pp. 487-489). Springer Nature. https://doi.org/10.1007/978-3-031-22203-0
PAOHVis (Valdivia et al., 2021) displays hypergraphs in a matrix where rows represent nodes (dots) and columns represent hyperedges (vertical lines). We propose extensions to PAOHVis for leveraging repeated hyperedges in non-simple hypergraphs, and displaying multiple node attributes. This is accomplished through two aggregation functions: count-based, which targets low-level detail, and binary, for high-level overview. In doing so, we introduce a domain-agnostic framework for consolidating hypergraphs by one or more categorical node attributes.
Reference:
- Valdivia, P., Buono, P., Plaisant, C., Dufournaud, N., Fekete, J.D. (2021). Analyzing dynamic hypergraphs with parallel aggregated ordered hypergraph visualization. IEEE Transactions on Visualization and Computer Graphics, 27(1), 1–13. https://doi.org/10.1109/TVCG.2019.2933196