Sep 2026· Zenodo (CERN European Organization for Nuclear Research)
Advanced Graph Neural Networks
Abstract
This paper proposes a novel approach to knowledge discovery and reasoning, termed Cognitive Graph-Based Knowledge Discovery & Reasoning (CGKR). The core idea is to construct a dynamic cognitive graph and leverage its reasoning capabilities alongside those of traditional knowledge graphs. The system integrates the structural knowledge of knowledge graphs with the dynamic relationships inherent in cognitive graphs. Employing graph neural networks (GNNs) for node embedding and relation learning, combined with logical inference algorithms for knowledge reasoning, this framework facilitates adaptive learning and deeper knowledge extraction. We demonstrate the potential of CGKR to overcome limitations inherent in static knowledge graphs, particularly in scenarios involving evolving information and nuanced relationships. The presented methodology offers a significant advancement in the field of knowledge representation and reasoning, promising improved accuracy and adaptability in complex knowledge discovery tasks. ---
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