Intelligent Q&A System Based on Knowledge Graph and Its Application in Education

Abstract

Question-answering (Q&A) systems enhance knowledge sharing but face accuracy challenges. This study proposes an intelligent Q&A framework combining a traditional retrieval module and a knowledge graph (KG) inference module, optimized through topic clustering and context awareness. Applied in education, the system integrates teacher feedback and extended functions (e.g., attention modeling, personalized recommendations). Teaching practice verifies its effectiveness and supports sustainable educational technology through knowledge reuse.