37 citations · 72 across the 7 of their papers we have counts for
7 papers
TeRo: A Time-aware Knowledge Graph Embedding via Temporal Rotation
Chengjin Xu, Mojtaba Nayyeri, Fouad Alkhoury +2
In the last few years, there has been a surge of interest in learning representations of entitiesand relations in knowledge graph (KG). However, the recent availability of temporal…
Temporal Knowledge Graph Embedding Model based on Additive Time Series Decomposition
Chengjin Xu, Mojtaba Nayyeri, Fouad Alkhoury +2
Knowledge Graph (KG) embedding has attracted more attention in recent years. Most KG embedding models learn from time-unaware triples. However, the inclusion of temporal informatio…
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…
Adaptive Margin Ranking Loss for Knowledge Graph Embeddings via a Correntropy Objective Function
Mojtaba Nayyeri, Xiaotian Zhou, Sahar Vahdati +2
Translation-based embedding models have gained significant attention in link prediction tasks for knowledge graphs. TransE is the primary model among translation-based embeddings a…
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…
Soft Marginal TransE for Scholarly Knowledge Graph Completion
Mojtaba Nayyeri, Sahar Vahdati, Jens Lehmann +1
Knowledge graphs (KGs), i.e. representation of information as a semantic graph, provide a significant test bed for many tasks including question answering, recommendation, and link…