A Double layered Crime Governance Model Based on BP Neural Network and TF-IDF Algorithm

The main methods of crime governance are pre prevention and post crackdown. With the development of intelligence and information technology, public security work has also ushered in new opportunities and challenges. This paper used intelligent algorithms and combines crime characteristics with existing big data resources in the public security system to propose a multidimensional facial recognition model based on TF-IDF algorithm, and combines it with a crime warning model based on BP neural network to form a closed crime governance chain of pre crime prevention and post crime investigation. This dual guarantee of crime governance is of great significance in reducing crime incidence, improving case solving accuracy and efficiency, enhancing people's sense of security, and ensuring social security and stability.