Buddhism attach great importance to the learning of medical knowledge and skills; the importance of it could be observed in “five sciences” (pañcavidyā) of ancient India, in which one of them is the “science of medicine” (cikitsā vidyā). The purpose of ‘medical learning’ in Buddhism, is to cure illness triggered by greed, aversion, and delusion (three poison), inflicted on body and mind of all living beings. Eventually, all ‘cured’ sentient beings will be guided and walk on the path to Buddhahood. Thus, Buddhism and Medical highly concern ‘suffering from illness’ of sentient beings. Though there are numerous texts related to medical in Buddhist scriptures, it is often scattered with no clear organization. The Dharma-Healing Database created by Dharma Drum Institute of Liberal Arts included 305 topic articles related to Buddhist medicine; however the categorization of the topic article relies on manual work, the standard of categorization became unclear, and the results of the categorization were not comprehensive. To solve the problem stated above, we attempted to apply hierarchical clustering in The Dharma-Healing Database and filtered out in the 90 volumes of scriptures from the Vinaya section of Taishō Tripiṭaka as the research object. Text clustering was applied to the Buddhist Medicine topic articles to create clusters. Through analyzing common keywords of each cluster, each cluster was given labels either manually or automatically. We then attempted to create a categorization structure for the topic articles. The research successfully established 10 clusters. Through the quantitative statistical methods, a basic structural categorization Buddhist Medicine text in Vinaya Pitaka was completed.
