Learning attention-enhanced relation-sensitive knowledge graph embeddings with variable receptive fields for link prediction
Knowledge graph embedding aims to predict missing links by learning representations of entities and relations. However, existing methods often struggle to effectively capture interaction features at multiple scales and to suppress redundant information among these multi-scale features, which hinders the model’s ability...
Wanxin Zeng, Yuxin Ye, Zhezhe Xing et al.
· Information Processing & Man... · 0 citations