129 citations · 663 across the 44 of their papers we have counts for
3 papers · 2 filters
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…
MDE: Multiple Distance Embeddings for Link Prediction in Knowledge Graphs
Afshin Sadeghi, Damien Graux, Hamed Shariat Yazdi +1
Over the past decade, knowledge graphs became popular for capturing structured domain knowledge. Relational learning models enable the prediction of missing links inside knowledge…