The Construction of Modern Administrative Law via Data Mining

Early administrative jurisprudence generally experienced a shift from administrative science to legal science, while modern administrative jurisprudence has shifted from judicial review to administrative process centered. In this paper, we introduce feature engineering technology into the construction model of administrative law based on data mining. The prior knowledge is introduced into the model through the artificially constructed effective features, and the neural network method can automatically extract features such as abstract features from the original input text. We propose a deep feature engineering method to combine the advantages of both in the study of relation extraction tasks. Experiments show that our method provides a powerful legal analysis tool, which helps to innovate the conceptual framework and theoretical system of traditional administrative law and establish a modern administrative law system that can explain the real-world administrative process.