Abstract: The standardized management technology platform for community correctional personnel is in the research stage. Due to the lack of actual data, community correctional personnel tag generation for building user portraits is not accurate enough. Therefore, based on the improved Stacking model fusion algorithm, this paper conducts modeling analysis after cleaning, sorting and feature selection for the community correctional personnel data of a citys judicial bureau. Furthermore, the prediction results of four labels, such as plead guilty attitude, mentality of society, mental health and corrective punishment case, are obtained. Comparing the prediction results with the experimental results, we can get the prediction accuracy. It shows the effectiveness and accuracy of the Stacking model fusion method for the generation of user labels of community correctional personnel.

Key words: community correctional personnel, Stacking model fusion, modeling analysis, tag generation