9 citations · 9 across the 3 of their papers we have counts for
4 papers
Leveraging Semantic Type Dependencies for Clinical Named Entity Recognition
Linh Le, Guido Zuccon, Gianluca Demartini +2
Previous work on clinical relation extraction from free-text sentences leveraged information about semantic types from clinical knowledge bases as a part of entity representations.…
Guiding Neural Entity Alignment with Compatibility
Bing Liu, Harrisen Scells, Wen Hua +3
Entity Alignment (EA) aims to find equivalent entities between two Knowledge Graphs (KGs). While numerous neural EA models have been devised, they are mainly learned using labelled…
High-quality Task Division for Large-scale Entity Alignment
Bing Liu, Wen Hua, Guido Zuccon +2
Entity Alignment (EA) aims to match equivalent entities that refer to the same real-world objects and is a key step for Knowledge Graph (KG) fusion. Most neural EA models cannot be…
ActiveEA: Active Learning for Neural Entity Alignment
Bing Liu, Harrisen Scells, Guido Zuccon +2
Entity Alignment (EA) aims to match equivalent entities across different Knowledge Graphs (KGs) and is an essential step of KG fusion. Current mainstream methods -- neural EA model…