Repeating-Local-Global History Network for Temporal Knowledge Graph Reasoning

The core message of this paper is to propose a model called Repeating-Local-Global History Network (RLGNet) that effectively integrates repeating, local, and global historical information to improve the accuracy of temporal knowledge graph reasoning.