基于电网技术标准知识图谱的神经符号推理方法研究

Research on Neural Symbolic Reasoning Method Based on Knowledge Graph of Power Grid Technical Standards

摘要: 电网技术标准知识兼具确定性规范约束与隐性关联模式两种形态，单一推理范式难以同时兼顾推理结果的可解释性与隐含关联的发现能力。神经符号推理范式通过将符号逻辑与神经网络相融合，为上述问题提供了系统化的解决思路。本文围绕电网技术标准知识图谱的推理需求，开展神经符号推理方法的体系化设计研究。针对标准条款的逻辑结构特征构建基于霍恩子句的领域启发式推理规则集，通过前向链匹配为候选关联提供可解释的规则支持信号；采用关系图卷积网络(R-GCN)与双线性解码器构建链路预测模型，发现图谱中未被显式标注的隐含关联；设计“候选生成–约束校验”两阶段融合机制，第一阶段对R-GCN概率得分与规则启发式支持两类软信号加权融合并排序，第二阶段以图谱中编码的强制性约束对候选进行硬过滤，使语义发现与合规约束在职责上相互分离。最后结合电网技术标准的典型业务场景，以典型示例说明所提框架的工作过程。

Abstract: The knowledge of power grid technical standards possesses both deterministic normative constraints and implicit association patterns. A single reasoning paradigm is difficult to simultaneously achieve interpretability of reasoning results and the ability to discover implicit associations. The neural symbolic reasoning paradigm, by integrating symbolic logic with neural networks, provides a systematic solution to the aforementioned problems. This paper focuses on the reasoning requirements of the power grid technical standards knowledge graph and conducts research on the systematic design of neural symbolic reasoning methods. A set of domain-specific heuristic reasoning rules based on Horn clauses is constructed according to the logical structural characteristics of standard clauses, providing interpretable rule support signals for candidate associations through forward chain matching. A link prediction model is constructed using a relational graph convolutional network (R-GCN) and a bilinear decoder to discover implicit associations that are not explicitly labeled in the graph. A two-stage fusion mechanism, namely “candidate generation - constraint verification”, is designed. In the first stage, two types of soft signals, namely R-GCN probability scores and rule-based heuristic support, are weighted and fused, and then ranked. In the second stage, hard filtering is applied to candidates based on the mandatory constraints encoded in the graph, separating semantic discovery and compliance constraints in terms of responsibilities. Finally, combined with typical business scenarios of power grid technical standards, typical examples are used to illustrate the working process of the proposed framework.