Every branch of mathematics employs some notion of a product that enables the com-
bination or decomposition of its elemental structures. In graph theory there are four main …

Community structure plays a significant role in the analysis of social networks and similar
graphs, yet this structure is little understood and not well captured by most models. We …

Similarity measures are used extensively in machine learning and data science algorithms.
The newly proposed graph Relative Hausdorff (RH) distance is a lightweight yet nuanced …

Increasing evidence suggests that an appropriate model for food webs, the network of
feeding links in a community of species, should take into account the inherent variability of …

Abstract A graph G=(V (G), E (G)) is called a k-dot product graph if there is a function f: V
(G)⟶ R k such that for any two distinct vertices u and v, one has f (u). f (v)≥ 1 if and only if …

We introduce a latent process model for time series of attributed random graphs for
characterizing multiple modes of association among a collection of actors over time. Two …

A rich class of network models associate each node with a low-dimensional latent
coordinate that controls the propensity for connections to form. Models of this type are well …

In this paper, we introduce a conceptual framework that model human social networks as an
undirected dot-product graph of independent individuals. Their relationships are only …

In this paper, we investigate a graph-theoretical model of social networks. The dot product
model assumes that two individuals are connected in the social network if their attributes or …

Over the last twenty years, as biological, technological, and social networks have risen in
prominence and importance, the study of complex networks has attracted researchers from a …