most citedInformed Multi-context Entity Alignment

28 citations · 30 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2022

EventEA: Benchmarking Entity Alignment for Event-centric Knowledge Graphs

Xiaobin Tian, Zequn Sun, Guangyao Li +1

Entity alignment is to find identical entities in different knowledge graphs (KGs) that refer to the same real-world object. Embedding-based entity alignment techniques have been d…

cs.CL20221 cited

Inductive Knowledge Graph Reasoning for Multi-batch Emerging Entities

Yuanning Cui, Yuxin Wang, Zequn Sun +4

Over the years, reasoning over knowledge graphs (KGs), which aims to infer new conclusions from known facts, has mostly focused on static KGs. The unceasing growth of knowledge in…

cs.CL2022

Dangling-Aware Entity Alignment with Mixed High-Order Proximities

Juncheng Liu, Zequn Sun, Bryan Hooi +5

We study dangling-aware entity alignment in knowledge graphs (KGs), which is an underexplored but important problem. As different KGs are naturally constructed by different sets of…

cs.AI2022

Ensemble Semi-supervised Entity Alignment via Cycle-teaching

Kexuan Xin, Zequn Sun, Wen Hua +4

Entity alignment is to find identical entities in different knowledge graphs. Although embedding-based entity alignment has recently achieved remarkable progress, training data ins…

cs.AI202228 cited

Informed Multi-context Entity Alignment

Kexuan Xin, Zequn Sun, Wen Hua +2

Entity alignment is a crucial step in integrating knowledge graphs (KGs) from multiple sources. Previous attempts at entity alignment have explored different KG structures, such as…

cs.CL2021

Principled Representation Learning for Entity Alignment

Lingbing Guo, Zequn Sun, Mingyang Chen +3

Embedding-based entity alignment (EEA) has recently received great attention. Despite significant performance improvement, few efforts have been paid to facilitate understanding of…