Abstract
With the deepening application of knowledge graph technology, in order to solve the problems that it is difficult to quickly obtain knowledge and complete the maintenance task, an intelligent auxiliary operation and maintenance system of power communication network based on knowledge graph is designed and implemented. The proposed system addresses effectively the two mentioned challenges accordingly by aggregating semantic information of different granularity in the constructed knowledge graph. Specifically, a Relation-Tuple-Entity Heterogeneous Graph Neural Network (SG-HGNN) is proposed to model effectively the different granularities of semantic information for knowledge reasoning. Comprehensive experiments which are conducted on the constructed knowledge graph demonstrate the effectiveness of the proposed framework. After the pilot application of the system, the problem hit rate and problem response time are significantly reduced, which greatly improves the operation and maintenance efficiency of power communication network.
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