Criminal Investigation Inference Model Based on Knowledge Graph and Weighted Bayesian Mechanism
With the rapid development of informatization and digitization,various artificial intelligence methods have been extensively applied in the field of modern public security.Among them,knowledge graphs,with their powerful knowledge representation and mathematical modeling capabilities,have greatly improved the interpretability of intelligent decision-making,making them a hot topic of research and application in this field.Bayesian inference models based on the Bayesian mechanism have always been important means for public security intelligence and criminal investigation analysis.In this paper,we introduce the knowledge graph of public security into the traditional Bayesian model.By fully considering the coupling of parameters,we effectively update the posterior probability with weighted updates,significantly improving the accuracy of inference.Taking the case of"Embroidered Spring Bag"in the novel"The Story of the Stone"as an empirical analysis,this paper scientifically reveals the truth of a classic case.The proposed scheme of using knowledge graph's search adaptive weighting effectively improves the efficiency of the Bayesian model,making it a beneficial attempt to empower intelligent public security with artificial intelligence.