2 citations · 2 across the 4 of their papers we have counts for
4 papers
Evaluating Cumulative Spectral Gradient as a Complexity Measure
Haji Gul, Abdul Ghani Naim, Ajaz Ahmad Bhat
Accurate estimation of dataset complexity is crucial for evaluating and comparing link prediction models for knowledge graphs (KGs). The Cumulative Spectral Gradient (CSG) metric d…
KG-EDAS: A Meta-Metric Framework for Evaluating Knowledge Graph Completion Models
Haji Gul, Abul Ghani Naim, Ajaz Ahmad Bhat
Knowledge Graphs (KGs) enable applications in various domains such as semantic search, recommendation systems, and natural language processing. KGs are often incomplete, missing en…
Evaluating Knowledge Graph Complexity via Semantic, Spectral, and Structural Metrics for Link Prediction
Haji Gul, Abul Ghani Naim, Ajaz Ahmad Bhat
Understanding dataset complexity is fundamental to evaluating and comparing link prediction models on knowledge graphs (KGs). While the Cumulative Spectral Gradient (CSG) metric, d…
A Contextualized BERT model for Knowledge Graph Completion
Haji Gul, Abdul Ghani Naim, Ajaz A. Bhat
Knowledge graphs (KGs) are valuable for representing structured, interconnected information across domains, enabling tasks like semantic search, recommendation systems and inferenc…