Structured synthetic data generation system and method

A structured synthetic data generation system, comprising a data preprocessing unit and a training and generation unit, wherein the data preprocessing unit is used for transforming each sample in original data into a vector representation and modeling a Bayesian network for describing a relation between features during the transformation process;

• the training and generation unit is used for training by means of the vector representation transformed from the original data to obtain a synthetic data generation model and generating a synthetic data record by means of the synthetic data generation model;
• wherein, the data preprocessing unit comprises a feature discretization module, a relation modeling module and a feature vector transformation module;
• the feature discretization module is used for discretizing a continuous feature to output a discretization result and information of the continuous feature lost during the discretization process;
• the relation modeling module is used for modeling the Bayesian network for describing the relation between features according to the discretization result input thereto;
• the feature vector transformation module is used for transforming the discretization result and the information of the continuous feature lost during the discretization process output by the feature discretization module into the vector representation by encoding and splicing;
• the training and generation unit comprises a generation model training module, a generation model generation module and a feature vector back-transformation module;
• the generation model training module is used for training a structured synthetic data generation model based on a generative adversarial network by means of the vector representation transformed from the original data;
• the generation model generation module is used for generating a synthetic data vector representation reserving the relation between features by means of the trained synthetic data generation model and the Bayesian network output by the relation modeling module;
• the feature vector back-transformation module is used for transforming the synthetic data vector representation into a synthetic data record identical in structure with the original data.