ABSTRACT: Typically, we think of idioms as colorful expressions whose literal interpretations don’t match their underlying meaning. However, many idiomatic expressions can be used either figuratively or literally, depending on their contexts. In this talk, we survey both supervised and unsupervised methods for training a classifier to automatically distinguish usages of idiomatic expressions. We will conclude with a discussion about some potential applications. BIO: Rebecca Hwa is an Associate Professor in the Department of Computer Science at the University of Pittsburgh. She received her BS in Computer Science and Engineering from UCLA in 1993, and her PhD in Computer Science from Harvard University in 2001. Her recent research focuses on understanding persuasion from a computational linguistics perspective. Some of her recent projects include: modeling student behaviors in revising argumentative essays, identifying symbolisms in visual rhetorics, and understanding idiomatic expressions. Dr. Hwa is a recipient of the NSF CAREER Award. Her work has also been supported by NIH and DARPA.

Hosted by: Professor Kai-Wei Chang