Abstract: The present invention relates to an interference-based method for knowledge graph completion and system thereof, wherein the method at least comprises: when performing sampling on a knowledge graph, constructing a knowledge graph completion model; performing model training and performance evaluation on the knowledge graph completion model; and performing prediction on missing elements of incomplete triples in the knowledge graph; the knowledge graph completion model is constructed through: based on optical interference and superposition principles, constructing a score function from data of superposed luminous intensities, mirroring the triples in the knowledge graph to a process of superposition of the luminous intensities, and differentiating between positives and negatives obtained during the sampling of the knowledge graph.

Abstract: The present invention relates to an interference-based method for knowledge graph completion and system thereof, wherein the method at least comprises: when performing sampling on a knowledge graph, constructing a knowledge graph completion model; performing model training and performance evaluation on the knowledge graph completion model; and performing prediction on missing elements of incomplete triples in the knowledge graph; the knowledge graph completion model is constructed through: based on optical interference and superposition principles, constructing a score function from data of superposed luminous intensities, mirroring the triples in the knowledge graph to a process of superposition of the luminous intensities, and differentiating between positives and negatives obtained during the sampling of the knowledge graph.