Knowledge Completion Method Based on Interference Principle

Knowledge graph completion is a crucial task in information retrieval and knowledge reasoning, but it often suffers from incomplete information. This paper introduces a novel approach to knowledge graph completion inspired by the principle of laser interference. The method aims to predict missing relationships within the knowledge graph, thereby enhancing its integrity and accuracy. We defined an ontology conceptual model for the laser domain and constructed a Knowledge Graph using knowledge acquisition, fusion, and storage technologies. The entities and relationships within the knowledge graph are mapped to represent light sources and intensities in the interference field. By simulating the constructive and destructive interference effects of two optical waves with the same frequency, we mimic the positive and negative cases found in knowledge graphs. This approach improves the accuracy and efficiency of the completion process.