January 20, 2023
Journal Article

Models and Methods for Sparse (Hyper) Network Science in Business, Industry, and Government

Abstract

The authors are hosting an AMS sponsored Mathematics Research Community (MRC) focusing on two themes that have garnered intense attention in network models of complex relational data: (1) how to faithfully model multi-way relations in hypergraphs, rather than only pairwise interactions in graphs; and (2) challenges posed by modelling networks with extreme sparsity. Here we introduce and explore these two themes and their challenges. We hope to generate interest from researchers in pure and applied mathematics and computer science.

Published: January 20, 2023

Citation

Aksoy S.G., A. Hagberg, C.A. Joslyn, B. Kay, E. Purvine, and S.J. Young. 2022. Models and Methods for Sparse (Hyper) Network Science in Business, Industry, and Government. Notices of the American Mathematical Society 69, no. 2:287-291. PNNL-SA-168162. doi:10.1090/noti2424

Research topics