274 citations · 579 across the 35 of their papers we have counts for
8 papers · 1 filter
Knowledge Association with Hyperbolic Knowledge Graph Embeddings
Zequn Sun, Muhao Chen, Wei Hu +3
Capturing associations for knowledge graphs (KGs) through entity alignment, entity type inference and other related tasks benefits NLP applications with comprehensive knowledge rep…
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…
Rule-Guided Graph Neural Networks for Recommender Systems
Xinze Lyu, Guangyao Li, Jiacheng Huang +1
To alleviate the cold start problem caused by collaborative filtering in recommender systems, knowledge graphs (KGs) are increasingly employed by many methods as auxiliary resource…
TransEdge: Translating Relation-contextualized Embeddings for Knowledge Graphs
Zequn Sun, Jiacheng Huang, Wei Hu +3
Learning knowledge graph (KG) embeddings has received increasing attention in recent years. Most embedding models in literature interpret relations as linear or bilinear mapping fu…
Realistic Re-evaluation of Knowledge Graph Completion Methods: An Experimental Study
Farahnaz Akrami, Mohammed Samiul Saeef, Qingheng Zhang +2
In the active research area of employing embedding models for knowledge graph completion, particularly for the task of link prediction, most prior studies used two benchmark datase…
A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs
Zequn Sun, Qingheng Zhang, Wei Hu +4
Entity alignment seeks to find entities in different knowledge graphs (KGs) that refer to the same real-world object. Recent advancement in KG embedding impels the advent of embedd…