Abstract by Stephen Cowley

Personal Infomation

Presenter's Name

Stephen Cowley

Degree Level



Jeff Lund
Wilson Fearn
Piper Armstrong
Emily Hales

Abstract Infomation


Computer Science

Faculty Advisor

Kevin Seppi


Cross-referencing using Fine-grained Topic Modeling


Cross-referencing, which links passages of text to other related passages, can be a valuable study aid for facilitating comprehension of a text. However, cross referencing requires first, a comprehensive thematic knowledge of the entire corpus, and second, a focused search through the corpus specifically to find such useful connections. Due to this, cross-reference resources are prohibitively expensive and exist only for the most well-studied texts (e.g. religious texts). We develop a topic-based system for automatically producing candidate cross-references which can be easily verified by human annotators. Our system utilizes fine grained topic modeling with thousands of highly nuanced and specific topics to identify verse pairs which are topically related. We demonstrate that our system can be cost effective compared to having annotators acquire the expertise necessary to produce cross-reference resources unaided.