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README.md [Model][Hetero] HAN (#868) Sep 27, 2019
main.py [Model][Hetero] HAN (#868) Sep 27, 2019
model.py [Model][Hetero] HAN (#868) Sep 27, 2019
model_hetero.py [Model][Hetero] HAN (#868) Sep 27, 2019
utils.py [Model][Hetero] HAN (#868) Sep 27, 2019

README.md

Heterogeneous Graph Attention Network (HAN) with DGL

This is an attempt to implement HAN with DGL's latest APIs for heterogeneous graphs. The authors' implementation can be found here.

Usage

python main.py for reproducing HAN's work on their dataset.

python main.py --hetero for reproducing HAN's work on DGL's own dataset.

Performance

Reference performance numbers for the ACM dataset:

micro f1 score macro f1 score
Paper 89.22 89.40
DGL 88.99 89.02
Softmax regression (own dataset) 89.66 89.62
DGL (own dataset) 91.51 91.66

We ran a softmax regression to check the easiness of our own dataset. HAN did show some improvements.

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