
시간 지식 그래프에서 진화적 사건 체인을 학습하기 위한 Transformer 기반 추론 모델 ECEformer를 제안한다.


coremsg

시간-지식-그래프에서-진화적-사건-체인-학습을-위한-transformer-기반-추론


시간 지식 그래프에서 진화적 사건 체인 학습을 위한 Transformer 기반 추론


title_rewrite


The core message of this paper is to propose an innovative Transformer-based network, dubbed ECEformer, that learns the evolutionary chain of events (ECE) to enhance the performance of temporal knowledge graph reasoning (TKGR).


enhancing-temporal-knowledge-graph-reasoning-by-learning-evolutionary-chains-of-events-with-transformer-based-models


Enhancing Temporal Knowledge Graph Reasoning by Learning Evolutionary Chains of Events with Transformer-based Models



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.


repeating-local-global-history-network-for-temporal-knowledge-graph-reasoning


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