MO-DMLHM: Multi-objective dynamic hypergraph modeling for cross-layer community detection in organizational networks
Authors:
- You-Hong LiYLYou-Hong Li
- Jian-Qiang WangJian-Qiang Wang
- Le GaoLGLe Gao
- Tian-Yu WangTWTian-Yu Wang
- Hao-Ming MoHMHao-Ming Mo
- 29 January 2026
- journal article
- Published by Elsevier in Information Sciences
- Vol. 739
Abstract
No abstract availableThis publication has 27 references indexed in Scilit:
- Community detection based on graph diffusion: A survey of definitions, challenges, and modelsExpert Systems with Applications, 2025
- Multilevel structure fusion for community detection in heterogeneous graphs via disrupting heterophilyKnowledge-Based Systems, 2025
- A robust rank aggregation framework for collusive disturbance based on community detectionInformation Processing & Management, 2025
- Developing a novel approach in estimating urban commute traffic by integrating community detection and hypergraph representation learningExpert Systems with Applications, 2024
- Evolutionary multi-objective overlapping community detection based on fusion of internal and external connectivity and correction of node intimacyApplied Soft Computing, 2024
- Two-type weight adjustments in MOEA/D for highly constrained many-objective optimizationInformation Sciences, 2021
- Non-dominated sorting on performance indicators for evolutionary many-objective optimizationInformation Sciences, 2021
- Evolutionary Multi-Objective Optimization Algorithm for Community Detection in Complex Social NetworksSN Computer Science, 2020
- Characterization and applications of temporal random walks on opportunistic networksComputer Networks, 2016
- Comparing partitionsJournal of Classification, 1985