Since real-world objects and their interactions are often multi-modal and multi-typed,
heterogeneous networks have been widely used as a more powerful, realistic, and generic …

The digital deep integration of cyber space, physical space and social space facilitates the
formation of Cyber–Physical–Social Systems (CPSS). Knowledge empowers CPSS to be …

Graph Neural Networks (GNNs) have recently enabled substantial advances in graph
learning. Despite their rich representational capacity, GNNs remain under-explored for large …

Group behavior modeling is an important research topic in the field of social network
analysis. Existing methods regarding this topic can only learn the static group preference …

The adoption of heterogeneous information networks (HINs) has gained popularity as a
means of modeling complex real-world systems with diverse interacting components …

The Heterogeneous Information Network (HIN) stands out as a prominent tool for depicting
interactions in real-world systems. Recently, representation learning on HINs has attracted …

The rapid development of the Internet and networking technologies greatly facilitates the
interactions among heterogeneous agents, while it also causes problems, such as the …

The research process includes many decisions, eg, how to entitle and where to publish the
paper. In this paper, we introduce a general framework for investigating the effects of such …

Heterogeneous graphs (HG) are an effective way of abstracting complex systems, including
social, biological, and economic systems. However, modeling these graphs is challenging …

Resource competition problems are often modeled using Colonel Blotto games. However,
Colonel Blotto games only simulate scenarios where players act simultaneously. In many …