Purpose/Significance To explore a quantitative analysis method for implicit diagnostic and therapeutic logic driven byknowledge graphs and graph computing，and to provide references for the digitalization and clinical application of ancient books of tradi-tional Chinese medicine(TCM). Method/Process A knowledge graph encompassing“syndromes，prescriptions，and medicinal herbs” is constructed. Graph computing methods such as degree centrality，Dice similarity，shortest paths search and closed-loop detection areemployed to quantitatively analyze the characteristics of core herbs and their compatibility networks. A intelligent service platform inte-grating retrieval and intelligent recommendation functionalities is developed. Result/Conclusion A knowledge graph comprising 480 en-tities and 711 relations is established. The implicit status of core herbs，the derivation lineage of prescriptions，and the“herb-syndrome”association logic within the ancient books are revealed through graph computing methods. The transformation of static histori-cal medical experience into dynamic auxiliary prescription is achieved through the platform. The proposed“graph-algorithm-platform” paradigm effectively bridges the gap between theoretical knowledge and clinical practice.