Single Chinese herbal medicine (CHM) is the basic element in the formulae of traditional Chinese medicine (TCM). How to acquire knowledge of a single CHM within the framework of TCM is a meaningful task. In TCM, Radix Astragali (RA) is frequently and widely used in clinical practice. In order to explore the associating rules between prescription and syndrome on RA with text mining technique, we downloaded the data set on RA from Chinese BioMedical literature database (also called SinoMed). Then, the rules of prescription corresponding to disease and syndrome on RA were mined out by executing data slicing algorithms. The mining results were visually demonstrated with software Cytoscape 2.8. Text mining, together with artificial reading for anti-noising and validation, is an important approach in exploring the rules of prescription corresponding to disease and syndrome. The results showed that RA was usually used in treating diseases of diabetes and cancers. For them, blood stasis due to qi deficiency was the main syndrome in TCM. Moreover, the results demonstrated associations among TCM syndrome, diseases and formulae associated with RA. These associated networks represented a variety of knowledge items which embodied the associating rules between prescription and syndrome on RA.