In the study, we propose using data mining to automatically identify cited references to Buddhist texts available through CBETA (Chinese Buddhist Electronic Text Association) embedded in the full-text Buddhist studies publications collected by DLMBS (Digital Library and Museum of Buddhist Studies), which now includes over 400,000 entries of Buddhist bibliographies in 45 languages, 65,000 of which are full-text. We believe that the cross-referencing between the Buddhist texts and related scholarly publications will provide great benefits for Buddhist scholarship. The users of the CBETA will have ready access to the relevant literature on the specific scripture they are studying. On the same token, the users of the DLMBS will be able to link directly to the exact scripture cited in the journal articles that they are reading. The aggregate co-citation data of Buddhist texts in the scholar publications also affords a rare opportunity to study the relationships among different Buddhist scriptures.