157 citations · 653 across the 20 of their papers we have counts for
4 papers · 1 filter
Deep Transfer Learning for Multi-source Entity Linkage via Domain Adaptation
Di Jin, Bunyamin Sisman, Hao Wei +2
Multi-source entity linkage focuses on integrating knowledge from multiple sources by linking the records that represent the same real world entity. This is critical in high-impact…
MultiImport: Inferring Node Importance in a Knowledge Graph from Multiple Input Signals
Namyong Park, Andrey Kan, Xin Luna Dong +2
Given multiple input signals, how can we infer node importance in a knowledge graph (KG)? Node importance estimation is a crucial and challenging task that can benefit a lot of app…
Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks
Namyong Park, Andrey Kan, Xin Luna Dong +2
How can we estimate the importance of nodes in a knowledge graph (KG)? A KG is a multi-relational graph that has proven valuable for many tasks including question answering and sem…
LinkNBed: Multi-Graph Representation Learning with Entity Linkage
Rakshit Trivedi, Bunyamin Sisman, Jun Ma +3
Knowledge graphs have emerged as an important model for studying complex multi-relational data. This has given rise to the construction of numerous large scale but incomplete knowl…