학술논문
Randomizing Hypergraphs Preserving Two-mode Clustering Coefficient
Document Type
Conference
Source
2023 IEEE International Conference on Big Data and Smart Computing (BigComp) BIGCOMP Big Data and Smart Computing (BigComp), 2023 IEEE International Conference on. :316-317 Feb, 2023
Subject
Language
ISSN
2375-9356
Abstract
Hypergraphs are data structures that capture the interactions between two or more nodes. By comparing random hypergraphs that preserve particular properties with an original hypergraph, we can analyze the impacts of those properties. In this study, we propose a method for generating random hypergraphs that preserve the pairwise joint degree distribution and the two-mode clustering coefficient. By the proposed method, we generated hypergraphs that preserve the average degree of the node and the degree of each node and approximately preserve the pairwise joint degree distribution and the two-mode clustering coefficient.