61 citations · 76 across the 7 of their papers we have counts for
5 papers · 1 filter
ProjB: An Improved Bilinear Biased ProjE model for Knowledge Graph Completion
Mojtaba Moattari, Sahar Vahdati, Farhana Zulkernine
Knowledge Graph Embedding (KGE) methods have gained enormous attention from a wide range of AI communities including Natural Language Processing (NLP) for text generation, classifi…
Trans4E: Link Prediction on Scholarly Knowledge Graphs
Mojtaba Nayyeri, Gokce Muge Cil, Sahar Vahdati +8
The incompleteness of Knowledge Graphs (KGs) is a crucial issue affecting the quality of AI-based services. In the scholarly domain, KGs describing research publications typically…
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…
5* Knowledge Graph Embeddings with Projective Transformations
Mojtaba Nayyeri, Sahar Vahdati, Can Aykul +1
Performing link prediction using knowledge graph embedding models has become a popular approach for knowledge graph completion. Such models employ a transformation function that ma…
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…