Researchers at the University of Texas at Austin (UT Austin) have partly developed quantitative criticism, a new approach for identifying subtle patterns to map out how ancient Latin and Greek texts relate to each other in an attempt to track the cultural evolution of literature.
"Our work seeks to harness the power of quantification and computation to describe those relationships at macro and micro levels not easily achieved by conventional reading alone," says UT Austin professor Pramit Chaudhuri.
The researchers generate literary profiles based on stylometric characteristics while applying machine-learning methods to understand the datasets. The team also uses machine learning to trace the maturation of Latin prose style.
Harvard University's Joseph Dexter says the project exemplifies the insight that, "computational methods can be repurposed to address questions of literary significance and style, which are often more ambiguous and open-ended."
From UT News
View Full Article
Abstracts Copyright © 2017 Information Inc., Bethesda, Maryland, USA
No entries found