IEEE

Towards Structure-Aware Model for Multi-Modal Knowledge Graph Completion

Abstract: Knowledge graphs (KGs) play a key role in promoting various multimedia and AI applications. However, with the explosive growth of multi-modal information, traditional knowledge graph ...
IEEE

Learning Resource Recommendation Model Based on Collaborative Knowledge Graph Attention Networks

Abstract: Aiming at the issue that most of the existing knowledge graph-based methods for personalized learning resource recommendations do not take full advantage of collaborative signals from ...
Journal of Medical Internet Research

Large Language Model–Driven Knowledge Graph Construction in Sepsis Care Using Multicenter Clinical Databases: Development and Usability Study

The resulting knowledge graph provides a robust framework for understanding sepsis, supporting clinical decision-making, and facilitating further research. The success of this approach underscores the ...
HackerNoon

The Race to Build AI’s Context Layer Is Really About Meaning

Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?
TMCnet

GreenCore Solutions Corp. (GSC) Announces AI Agent CPG Knowledge Graph and Agent Skills; Signs Definitive Asia-Pacific Joint Venture

TORONTO and BARCELONA, SPAIN and SYDNEY, June 29, 2026 /CNW/ - GreenCore Solutions Corp. (GSC), a leader in AI Agents for CPG manufacturers, today announced the launch of the industry's first CPG ...
GitHub

DiffKG: Knowledge Graph Diffusion Model for Recommendation

This is the PyTorch implementation for DiffKG proposed in the paper DiffKG: Knowledge Graph Diffusion Model for Recommendation, which is accepted by WSDM 2024 Oral. Yangqin Jiang, Yuhao Yang, Lianghao ...