48 citations · 172 across the 15 of their papers we have counts for
6 papers · 1 filter
Meta-Learning Based Knowledge Extrapolation for Temporal Knowledge Graph
Zhongwu Chen, Chengjin Xu, Fenglong Su +2
In the last few years, the solution to Knowledge Graph (KG) completion via learning embeddings of entities and relations has attracted a surge of interest. Temporal KGs(TKGs) exten…
Time-aware Graph Neural Networks for Entity Alignment between Temporal Knowledge Graphs
Chengjin Xu, Fenglong Su, Jens Lehmann
Entity alignment aims to identify equivalent entity pairs between different knowledge graphs (KGs). Recently, the availability of temporal KGs (TKGs) that contain time information…
Geometric Algebra based Embeddings for Static and Temporal Knowledge Graph Completion
Chengjin Xu, Mojtaba Nayyeri, Yung-Yu Chen +1
Recent years, Knowledge Graph Embeddings (KGEs) have shown promising performance on link prediction tasks by mapping the entities and relations from a Knowledge Graph (KG) into a g…
Multiple Run Ensemble Learning with Low-Dimensional Knowledge Graph Embeddings
Chengjin Xu, Mojtaba Nayyeri, Sahar Vahdati +1
Among the top approaches of recent years, link prediction using knowledge graph embedding (KGE) models has gained significant attention for knowledge graph completion. Various embe…
Toward Understanding The Effect Of Loss function On Then Performance Of Knowledge Graph Embedding
Mojtaba Nayyeri, Chengjin Xu, Yadollah Yaghoobzadeh +2
Knowledge graphs (KGs) represent world's facts in structured forms. KG completion exploits the existing facts in a KG to discover new ones. Translation-based embedding model (Trans…
LogicENN: A Neural Based Knowledge Graphs Embedding Model with Logical Rules
Mojtaba Nayyeri, Chengjin Xu, Jens Lehmann +1
Knowledge graph embedding models have gained significant attention in AI research. Recent works have shown that the inclusion of background knowledge, such as logical rules, can im…