Hypergraph Modeling

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