Graph Star Net for Generalized Multi-Task Learning
In this work, we present graph star net (GraphStar), a novel and unified graph neural net architecture which utilizes message-passing relay and attention mechanism for multiple prediction tasks - node classification, graph classification and link prediction. GraphStar addresses many earlier challenges facing graph neural nets and achieves non-local representation without increasing the model depth or bearing heavy computational costs. We also propose a new method to tackle topic-specific sentiment analysis based on node classification and text classification as graph classification. Our work shows that 'star nodes' can learn effective graph-data representation and improve on current methods for the three tasks. Specifically, for graph classification and link prediction, GraphStar outperforms the current state-of-the-art models by 2-5% on several key benchmarks.
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Cora
OHSUMED
MR
Results from the Paper
| Task | Dataset | Model | Metric Name | Metric Value | Global Rank | Uses Extra Training Data |
Benchmark |
|---|---|---|---|---|---|---|---|
| Text Classification | 20NEWS | GraphStar | Accuracy | 86.9 | # 8 | ||
| Node Classification | Citeseer | GraphStar | Accuracy | 71.0 | # 57 | ||
| Link Prediction | Citeseer (biased evaluation) | GraphStar (double weight on positive examples) | AUC | 97.47 | # 1 | ||
| AP | 97.93 | # 1 | |||||
| Accuracy | 97.7 | # 1 | |||||
| Node Classification | Cora | GraphStar | Accuracy | 82.1% | # 55 | ||
| Link Prediction | Cora (biased evaluation) | GraphStar (double weight on positive examples) | AUC | 95.65 | # 1 | ||
| AP | 96.15 | # 1 | |||||
| Accuracy | 95.9 | # 1 | |||||
| Graph Classification | D&D | GraphStar | Accuracy | 79.60% | # 15 | ||
| Graph Classification | ENZYMES | GraphStar | Accuracy | 67.1% | # 13 | ||
| Sentiment Analysis | IMDb | GraphStar | Accuracy | 96.0 | # 4 | ||
| Sentiment Analysis | MR | GraphStar | Accuracy | 76.6 | # 14 | ||
| Graph Classification | MUTAG | GraphStar | Accuracy | 91.2% | # 14 | ||
| Text Classification | Ohsumed | GraphStar | Accuracy | 64.2 | # 7 | ||
| Node Classification | PPI | GraphStar | F1 | 99.4 | # 7 | ||
| Graph Classification | PROTEINS | GraphStar | Accuracy | 77.90% | # 19 | ||
| Node Classification | Pubmed | GraphStar | Accuracy | 77.2% | # 59 | ||
| Link Prediction | Pubmed (biased evaluation) | GraphStar (double weight on positive examples) | AUC | 97.67 | # 1 | ||
| AP | 98.64 | # 1 | |||||
| Accuracy | 98.16 | # 1 | |||||
| Text Classification | R52 | GraphStar | Accuracy | 95.00 | # 2 | ||
| Text Classification | R8 | GraphStar | Accuracy | 97.4 | # 12 |
