Hypergraph Modeling

Abstract Hypergraph modeling is the fundamental task in hypergraph computation, which targets on establishing a high-quality hypergraph structure to accurately formulate the high-order correlation among data. In this section, we introduce different hypergraph modeling methods to show how to build hypergraphs using various pieces of information, such as features, attributes, and/or graphs. These methods are organized into two broad categories, depending on whether these correlations are explicit or implicit, to distinguish the similarities and differences. We then further discuss different hypergraph structure optimization and generation methods, such as adaptive hypergraph modeling, generative hypergraph modeling, and knowledge hypergraph generation.