Random clique covers for graphs with local density and global sparsity

Large real-world graphs tend to be sparse, but they often contain densely connected subgraphs and exhibit high clustering coefficients. While recent random graph models can capture this sparsity, they ignore the local density. We show that models based on random edge clique covers can capture both global sparsity and local density, and are an appropriate modeling tool for many real-world graphs.