1 research outputs found
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.Comment: 6 figures 1 table 8 page