| Ekaterina Shutova |
| Fri 04 Dec 2015, 11:00 - 12:30 |
| Informatics Forum (IF-4.31/4.33) |
If you have a question about this talk, please contact: Diana Dalla Costa (ddallac)
ABSTRACT:
Besides making our thoughts more vivid and filling our communication with richer imagery, metaphor plays a fundamental structural role in our cognition, helping us organise and project knowledge. For example, when we say “a well-oiled political machine”, we view the concept of political system in terms of a mechanism and transfer inferences from the domain of mechanisms onto our reasoning about political processes. Highly frequent in text, metaphorical language represents a significant challenge for natural language processing (NLP) systems; and large-scale, robust and accurate metaphor processing tools are needed to improve the overall quality of semantic interpretation in today’s language technology. In this talk I will introduce statistical models of metaphor identification and interpretation and discuss how statistical techniques can be applied to identify patterns of the use of metaphor in linguistic data and to generalise its higher-level mechanisms from text.
BIOGRAPHY:
Ekaterina Shutova is a Leverhulme Early Career Fellow at the University of Cambridge Computer Laboratory. Her research is in the area of natural language processing with a specific focus on computational semantics and figurative language processing using statistical learning. Previously, she worked at the International Computer Science Institute and the Institute for Cognitive and Brain Sciences at the University of California, Berkeley and the Department of Theoretical and Applied Linguistics at the University of Cambridge. Ekaterina received her PhD in Computer Science from the University of Cambridge in 2011 and her doctoral dissertation concerned computational modelling of figurative language.