Complex networks pervade various real-world systems, from the natural environment to
human societies. The essence of these networks is in their ability to transition and evolve …

Hyperedges, as extensions of pairwise edges, can characterize higher-order relations
among multiple individuals. Due to the necessity of hypergraph detection in practical …

Detecting social bots has evolved into a pivotal yet intricate task, aimed at combating the
dissemination of misinformation and preserving the authenticity of online interactions. While …

With the booming development of social media, temporal link prediction (TLP), as a core
technology, has been receiving increasing attention. However, current methods are based …

Traditional social link prediction models primarily concentrate on the adjacency features of
the network, overlooking the rich high-order structural information within. Therefore, the …

Dynamic recommendation systems, where users interact with items continuously over time,
have been widely deployed in real-world online streaming applications. The burst of …

This research introduces the Variational Graph Attention Dynamics (VarGATDyn),
addressing the complexities of dynamic graph representation learning, where existing …

With the increasing magnitude and complexity of data, the importance of higher-order
networks is increasingly prominent. Dynamic hyperedge prediction reveals potential higher …

Temporal Heterogeneous Networks play a crucial role in capturing the dynamics and
heterogeneity inherent in various real-world complex systems, rendering them a noteworthy …

Recently, higher order patterns have played an important role in network structure analysis.
The simplices in higher order patterns enrich dynamic network modeling and provide strong …