Advancing rule learning in knowledge graphs with structure-aware graph transformer

Kang Xu, Miqi Chen, Yifan Feng, Zhenjiang Dong

Abstract: Highlights•We proposed SARL, a structure-aware graph transformer for rule learning on KGs.•We proposed generalized attention mechanism, which is replaceable for flexibility.•SARL outperforms baselines and is easily applicable to other KG reasoning tasks.