International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Review on Implementation of Hypergraph Neural Network in Different Domains

Ashwini Ashok mahindM. Tech Student, Ashokrao Mane Group of Institutions, Vathar, Kolhapur, Maharashtra, India

Vol 8 No 10 (2024): Volume 8, Issue 10, October 2024 | Pages: 163-167

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 22-10-2024

doi Logo doi.org/10.47001/IRJIET/2024.810022

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Abstract

Hypergraph neural networks (HGNNs) have emerged as a powerful framework for modeling complex, high-order relationships in data that go beyond traditional graph structures. This review examines the implementation and applications of HGNNs across diverse domains. We analyze how HGNNs have been adapted to capture multi-way interactions in fields such as social network analysis, bioinformatics, computer vision, and recommendation systems. Key architectural variations and training approaches are discussed, along with domain-specific challenges and solutions. We also explore how HGNNs compare to traditional graph neural networks in terms of expressiveness and computational efficiency. Finally, we highlight open research questions and promising future directions for expanding the use of HGNNs to new problem domains. This comprehensive overview aims to provide researchers and practitioners with insights into effectively leveraging hypergraph-based deep learning for complex relational data.

Keywords

Hypergraph neural networks (HGNNs), Multi-modal Data Analysis, Contrastive Learning


Citation of this Article

Ashwini Ashok mahind. (2024). Review on Implementation of Hypergraph Neural Network in Different Domains. International Research Journal of Innovations in Engineering and Technology - IRJIET, 8(10), 163-167. Article DOI https://doi.org/10.47001/IRJIET/2024.810022

Licence Copyright (c) 2026 International Research Journal of Innovations in Engineering and Technology creative common licence This work is licensed under Creative common Attribution Non Commercial 4.0 Internation Licence
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