Research on the Application of AI-Based Intelligent Decision Support Systems in E-Government Services

Abstract

The rapid digitalization of public administration has spurred growing interest in intelligent decision support systems (IDSS) for e-government. However, current solutions often suffer from limited trust-awareness, weak legal interpretability, and inadequate integration of citizen feedback, restricting their policy relevance and adoption. To address these challenges, the authors propose IA-DSS-EG, an Integrated AI-based Decision Support System designed for multi-dimensional, human-centered decision-making in digital governance. The framework incorporates five synergistic modules: Government Role Mapping for administrative function classification, a Data-Driven Engine for fiscal impact forecasting, a Trust-Aware Filter leveraging public sentiment data, Semantic Knowledge Graph Reasoning to ensure legal compatibility, and a Reinforcement Learning loop for feedback-based policy optimization. They evaluate IA-DSS-EG across five real-world datasets and compare it against eight leading baseline models.