Nowadays, it has been demonstrated that graph neural networks (GNNs) are a powerful tool
for graph representation learning. However, most GNN models are shallow ones because …

People's social life has become more embedded in dynamic online communities. Each
online community can be viewed as a temporal online social network (OSN). The interaction …

RoleSim and SimRank are among the popular graph-theoretic similarity measures with
many applications in, eg, web search, collaborative filtering, and sociometry. While RoleSim …

RoleSim and SimRank are popular graph-theoretic similarity measures with many
applications in, eg, web search, collaborative filtering, and sociometry. While RoleSim …

Role-based similarity search, predicated on the topological structure of graphs, is a highly
effective and widely applicable technique for various real-world information extraction …

Role is a fundamental concept in the analysis of the behavior and function of interacting
entities in complex networks. Role discovery is the task of uncovering the hidden roles of …

As a fundamental issue in network analysis, structural node similarity has received much
attention in academia and is adopted in a wide range of applications. Among these …

The conundrum of quantifying pairwise similarity based on network topology arises in many
graph mining applications, eg, community detection. RoleSim is an arresting similarity …

Role is a fundamental concept in the analysis of the behavior and function of interacting
entities in complex networks. Role discovery is the task of uncovering the hidden roles of …

Defining similarity between two nodes is a highly subjective area of research. We define
similarity between two nodes in a network as the measure of how similar these two nodes …