SM-GNN prunes multi-view GNNs to pure propagation, cutting training time while outperforming prior MKGC accuracies on two ...
Knowledge Graph, Large Language Model, BERT, Knowledge Management, Small and Medium-Sized Enterprises, Accounting, Supply Chain Management Zheng, Y. (2026) Knowledge Graph Application in KM for ...
A new artificial intelligence (AI) method called BioPathNet helps researchers systematically search large biological data ...
ProPEX-RAG is a prompt-driven, entity-guided RAG framework that emphasizes the role of prompt design in improving retrieval and reasoning across large knowledge graphs. Our approach unifies symbolic ...
Abstract: Knowledge Graphs (KGs), with their intricate hierarchies and semantic relationships, present unique challenges for graph representation learning, necessitating tailored approaches to ...
As for the AI bubble, it is coming up for conversation because it is now having a material effect on the economy at large. Some accounts estimate that AI is driving 90% of US GDP growth, while others ...
Abstract: Knowledge graph construction is aimed at storing and representing the knowledge of the objective world in a structured form. Existing methods for automatic construction of knowledge graphs ...
A deep learning system that uses Graph Attention Networks (GAT) and LSTM to predict volatility spillovers across the Electric Vehicle supply chain by modeling real supplier relationships extracted ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback