Classification of Edge-dependent Labels of Nodes in Hypergraphs
Minyoung Choe, Sunwoo Kim, Jaemin Yoo, Kijung Shin
Abstract
A hypergraph is a data structure composed of nodes and hyperedges, where each hyperedge is an any-sized subset of nodes. Due to the flexibility in hyperedge size, hypergraphs represent group interactions (e.g., co-authorship by more than two authors) more naturally and accurately than ordinary graphs. Interestingly, many real-world systems modeled as hypergraphs contain edge-dependent node labels, i.e., node labels that vary depending on hyperedges. For example, on co-authorship datasets, the same author (i.e., a node) can be the primary author in a paper (i.e., a hyperedge) but the corresponding author in another paper (i.e., another hyperedge).
Topics & Concepts
HypergraphNode (physics)Enhanced Data Rates for GSM EvolutionFlexibility (engineering)Computer scienceTheoretical computer scienceCombinatoricsMathematicsDiscrete mathematicsArtificial intelligenceStatisticsPhysicsQuantum mechanicsComplex Network Analysis TechniquesAdvanced Graph Neural NetworksBioinformatics and Genomic Networks