most citedTime-aware Graph Neural Networks for Entity Alignment between Temporal Knowledge Graphs

48 citations · 56 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2023

Incorporating Structured Sentences with Time-enhanced BERT for Fully-inductive Temporal Relation Prediction

Zhongwu Chen, Chengjin Xu, Fenglong Su +2

Temporal relation prediction in incomplete temporal knowledge graphs (TKGs) is a popular temporal knowledge graph completion (TKGC) problem in both transductive and inductive setti…

cs.LG2023★ 2 cited

Toward Practical Entity Alignment Method Design: Insights from New Highly Heterogeneous Knowledge Graph Datasets

Xuhui Jiang, Chengjin Xu, Yinghan Shen +7

The flourishing of knowledge graph applications has driven the need for entity alignment (EA) across KGs. However, the heterogeneity of practical KGs, characterized by differing sc…

cs.AI2023★ 1 cited

Meta-Learning Based Knowledge Extrapolation for Temporal Knowledge Graph

Zhongwu Chen, Chengjin Xu, Fenglong Su +2

In the last few years, the solution to Knowledge Graph (KG) completion via learning embeddings of entities and relations has attracted a surge of interest. Temporal KGs(TKGs) exten…

cs.LG2022★ 5 cited

TFLEX: Temporal Feature-Logic Embedding Framework for Complex Reasoning over Temporal Knowledge Graph

Xueyuan Lin, Chengjin Xu, Haihong E +6

Multi-hop logical reasoning over knowledge graph (KG) plays a fundamental role in many artificial intelligence tasks. Recent complex query embedding (CQE) methods for reasoning foc…

cs.AI2022★ 48 cited

Time-aware Graph Neural Networks for Entity Alignment between Temporal Knowledge Graphs

Chengjin Xu, Fenglong Su, Jens Lehmann

Entity alignment aims to identify equivalent entity pairs between different knowledge graphs (KGs). Recently, the availability of temporal KGs (TKGs) that contain time information…