8 citations · 36 across the 9 of their papers we have counts for
5 papers · 1 filter
Logic and Commonsense-Guided Temporal Knowledge Graph Completion
Guanglin Niu, Bo Li
A temporal knowledge graph (TKG) stores the events derived from the data involving time. Predicting events is extremely challenging due to the time-sensitive property of events. Be…
CAKE: A Scalable Commonsense-Aware Framework For Multi-View Knowledge Graph Completion
Guanglin Niu, Bo Li, Yongfei Zhang +1
Knowledge graphs store a large number of factual triples while they are still incomplete, inevitably. The previous knowledge graph completion (KGC) models predict missing links bet…
Perform Like an Engine: A Closed-Loop Neural-Symbolic Learning Framework for Knowledge Graph Inference
Guanglin Niu, Bo Li, Yongfei Zhang +1
Knowledge graph (KG) inference aims to address the natural incompleteness of KGs, including rule learning-based and KG embedding (KGE) models. However, the rule learning-based mode…
Relational Learning with Gated and Attentive Neighbor Aggregator for Few-Shot Knowledge Graph Completion
Guanglin Niu, Yang Li, Chengguang Tang +7
Aiming at expanding few-shot relations' coverage in knowledge graphs (KGs), few-shot knowledge graph completion (FKGC) has recently gained more research interests. Some existing mo…
Joint Semantics and Data-Driven Path Representation for Knowledge Graph Inference
Guanglin Niu, Bo Li, Yongfei Zhang +4
Inference on a large-scale knowledge graph (KG) is of great importance for KG applications like question answering. The path-based reasoning models can leverage much information ov…