4 papers
Efficient Computation of Maximum Flexi-Clique in Networks
Song Kim, Hyewon Kim, Kaiqiang Yu +4
Discovering large cohesive subgraphs is a key task for graph mining. Existing models, such as clique, k-plex, and γ-quasi-clique, use fixed density thresholds that overlook the na…
Experimental Analysis and Evaluation of Cohesive Subgraph Discovery
Dahee Kim, Song Kim, Jeongseon Kim +4
Retrieving cohesive subgraphs in networks is a fundamental problem in social network analysis and graph data management. These subgraphs can be used for marketing strategies or rec…
Uncovering High-Order Cohesive Structures: Efficient (k,g)-Core Computation and Decomposition for Large Hypergraphs
Dahee Kim, Hyewon Kim, Song Kim +4
Hypergraphs, increasingly utilised to model complex and diverse relationships in modern networks, have gained significant attention for representing intricate higher-order interact…
Cohesive Subgraph Discovery in Hypergraphs: A Locality-Driven Indexing Framework
Song Kim, Dahee Kim, Taejoon Han +3
Hypergraphs, increasingly utilised for modelling complex and diverse relationships in modern networks, gain much attention representing intricate higher-order interactions. Among v…