Knowledge Graph Construction and Semantic Reasoning for Traditional Chinese Medicine

Traditional Chinese Medicine (TCM) contains rich but unstructured medical knowledge, making it difficult to apply in intelligent systems. This paper proposes a framework for constructing a TCM knowledge graph and performing semantic reasoning to infer relationships among symptoms, syndromes, and prescriptions. Experiments on open TCM datasets demonstrate that the framework effectively organizes TCM knowledge and provides interpretable recommendations for diagnosis and treatment.