hybrid-graph-benchmark
This is a benchmark dataset for evaluating hybrid graph (a unified definition for higher-order graphs, including hypergraphs and hierarchical graphs) learning algorithms. It contains:
- 23 real-world higer-order graphs from the domains of social media (MUSAE), biology (GRAND), and e-commerce (Amazon).
- Built-in functionalities for preprocessing hybrid-graphs
- A framework to easily train and evaluate Graph Neural Networks
Get started by installing from GitHub
Modules
Hybrid Graph Datasets
Hybrid Graph Evaluation Framework
Summary
Click the dataset name to see more details:
| Name | #Graphs | #Nodes | #Edges | #Hyperedges | Avg. Node Degree | Avg. Hyperedge Degree | Clustering Coef. | Task Type |
|---|---|---|---|---|---|---|---|---|
| MUSAE-GitHub | 1 | 37,700 | 578,006 | 223,672 | 30.7 | 4.6 | 0.168 | Node Classification |
| MUSAE-Facebook | 1 | 22,470 | 342,004 | 236,663 | 30.4 | 9.9 | 0.360 | Node Classification |
| MUSAE-Twitch | 6 | 5,686 | 143,038 | 110,142 | 50.6 | 6.0 | 0.210 | Node Classification |
| MUSAE-Wiki | 3 | 6,370 | 266,998 | 118,920 | 88.8 | 14.4 | 0.413 | Node Regression |
| GRAND-Tissues | 6 | 5,931 | 5,926 | 11,472 | 2.0 | 1.3 | 0.000 | Node Classification |
| GRAND-Diseases | 4 | 4,596 | 6,252 | 7,743 | 2.7 | 1.3 | 0.000 | Node Classification |
| Amazon-Computers | 1 | 10,226 | 55,324 | 10,226 | 10.8 | 4.0 | 0.249 | Node Classification |
| Amazon-Photos | 1 | 6,777 | 45,306 | 6,777 | 13.4 | 4.8 | 0.290 | Node Classification |
License
Source code: MIT license
MUSAE & GRAND datasets: GPLv3 license
Amazon datasets: Amazon Service license
Cite This Project
@article{Li2023HybridGraph,
title={Hybrid Graph: A Unified Graph Representation with Datasets and Benchmarks for Complex Graphs},
author={Zehui Li and
Xiangyu Zhao and
Mingzhu Shen and
Guy-Bart Stan and
Pietro Li{\`o} and
Yiren Zhao},
journal={arXiv preprint arXiv:2306.05108},
year={2023}
}