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Multi-Order Relations Hyperbolic Fusion for Heterogeneous Graphs

Published: 21 October 2023 Publication History

Abstract

Heterogeneous graphs with multiple node and edge types are prevalent in real-world scenarios. However, most methods use meta-paths on the original graph structure to learn information in heterogeneous graphs, and these methods only consider pairwise relations and rely on meta-paths. In this paper, we use simplicial complexes to extract higher-order relations containing multiple nodes from heterogeneous graphs. We also discover power-law structures in both the heterogeneous graph and the extracted simplicial complex. Thus, we propose the Simplicial Hyperbolic Attention Network (SHAN), a graph neural network for heterogeneous graphs. SHAN extracts simplicial complexes and the original graph structure from the heterogeneous graph to represent multi-order relations between nodes. Next, SHAN uses hyperbolic multi-perspective attention to learn the importance of different neighbors and relations in hyperbolic space. Finally, SHAN integrates multi-order relations to obtain a more comprehensive node representation. We conducted extensive experiments to verify the effectiveness of SHAN and the results of node classification experiments on three publicly available heterogeneous graph datasets demonstrate that SHAN outperforms representative baseline models.

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Cited By

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  • (2024)Hyperbolic Heterogeneous Graph Attention NetworksCompanion Proceedings of the ACM on Web Conference 202410.1145/3589335.3651522(561-564)Online publication date: 13-May-2024
  • (2024)Representation of Multirelations of Geographic Scenes Based on Hyperbolic SpaceIEEE Transactions on Geoscience and Remote Sensing10.1109/TGRS.2024.340784362(1-13)Online publication date: 2024

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cover image ACM Conferences
CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management
October 2023
5508 pages
ISBN:9798400701245
DOI:10.1145/3583780
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Published: 21 October 2023

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  1. heterogeneous graph
  2. hyperbolic graph attention
  3. simplicial complex

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  • (2024)Hyperbolic Heterogeneous Graph Attention NetworksCompanion Proceedings of the ACM on Web Conference 202410.1145/3589335.3651522(561-564)Online publication date: 13-May-2024
  • (2024)Representation of Multirelations of Geographic Scenes Based on Hyperbolic SpaceIEEE Transactions on Geoscience and Remote Sensing10.1109/TGRS.2024.340784362(1-13)Online publication date: 2024

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