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20192021
most citedNeighborhood Matching Network for Entity Alignment

12 citations · 23 across the 3 of their papers we have counts for

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Showing cs.CLShow all

5 papers · 1 filter

cs.CL20218 cited

SIRE: Separate Intra- and Inter-sentential Reasoning for Document-level Relation Extraction

Shuang Zeng, Yuting Wu, Baobao Chang

Document-level relation extraction has attracted much attention in recent years. It is usually formulated as a classification problem that predicts relations for all entity pairs i…

cs.CL20213 cited

Everything Has a Cause: Leveraging Causal Inference in Legal Text Analysis

Xiao Liu, Da Yin, Yansong Feng +2

Causal inference is the process of capturing cause-effect relationship among variables. Most existing works focus on dealing with structured data, while mining causal relationship…

cs.CL202012 cited

Neighborhood Matching Network for Entity Alignment

Yuting Wu, Xiao Liu, Yansong Feng +2

Structural heterogeneity between knowledge graphs is an outstanding challenge for entity alignment. This paper presents Neighborhood Matching Network (NMN), a novel entity alignmen…

cs.CL2019

Jointly Learning Entity and Relation Representations for Entity Alignment

Yuting Wu, Xiao Liu, Yansong Feng +2

Entity alignment is a viable means for integrating heterogeneous knowledge among different knowledge graphs (KGs). Recent developments in the field often take an embedding-based ap…

cs.CL2019

Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs

Yuting Wu, Xiao Liu, Yansong Feng +3

Entity alignment is the task of linking entities with the same real-world identity from different knowledge graphs (KGs), which has been recently dominated by embedding-based metho…