Towards a Unified Temporal and Event Logic Paradigm for Multi-Hop Path Reasoning in Knowledge Graphs

• DOI: 10.3390/electronics14030516
• Publication Date: 2025-01-27T14:42:23Z
• Authors: Yajian Zeng; Xiaorong Hou; Xinrui Wang; Junying Li

Path reasoning in knowledge graphs is a pivotal task for uncovering complex relational patterns and facilitating advanced inference processes. It also holds significant potential domains such as power electronics, where real-time over dynamic, evolving data essential advancing topology design application systems. Despite its importance, traditional approaches often encounter substantial limitations when applied to time-sensitive scenarios. These models typically fail adequately capture intricate logical dependencies demonstrate suboptimal performance data-constrained environments. To address these challenges, we introduce Path-Reasoning Logic (PRlogic), an innovative framework that seamlessly integrates rule-based with cutting-edge neural network methodologies. PRlogic enhances path by leveraging context-aware association adept at handling temporal event-driven attributes, enabling improved dynamic systems IoT-based electronics smart grids. This adaptability allows the better accommodate structures, significantly improving accuracy under resource-scarce conditions. Furthermore, employs multi-stage refinement strategy, harmonizing logic-based rules learned contextual representations achieve heightened robustness scalability. Comprehensive experiments on widely-recognized benchmark datasets validate superiority of PRlogic, demonstrating consistent outperformance existing tasks. results underscore efficacy incorporating logic-driven mechanisms into graph highlight PRlogic’s powerful solution applications