9 citations · 16 across the 3 of their papers we have counts for
3 papers
cs.CL2020★ 6 cited
Global-to-Local Neural Networks for Document-Level Relation Extraction
Difeng Wang, Wei Hu, Ermei Cao +1
Relation extraction (RE) aims to identify the semantic relations between named entities in text. Recent years have witnessed it raised to the document level, which requires complex…
cs.IR2020★ 1 cited
Open Knowledge Enrichment for Long-tail Entities
Ermei Cao, Difeng Wang, Jiacheng Huang +1
Knowledge bases (KBs) have gradually become a valuable asset for many AI applications. While many current KBs are quite large, they are widely acknowledged as incomplete, especiall…
cs.CL2018★ 9 cited
Recurrent Skipping Networks for Entity Alignment
Lingbing Guo, Zequn Sun, Ermei Cao +1
We consider the problem of learning knowledge graph (KG) embeddings for entity alignment (EA). Current methods use the embedding models mainly focusing on triple-level learning, wh…