Paper: Discriminating Rhetorical Analogies in Social Media

ACL ID E14-1059
Title Discriminating Rhetorical Analogies in Social Media
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

Analogies are considered to be one of the core concepts of human cognition and communica- tion, and are very efficient at encoding com- plex information in a natural fashion. How- ever, computational approaches towards large- scale analysis of the semantics of analogies are hampered by the lack of suitable corpora with real-life example of analogies. In this paper we therefore propose a workflow for discriminat- ing and extracting natural-language analogy statements from the Web, focusing on analo- gies between locations mined from travel re- ports, blogs, and the Social Web. For realizing this goal, we employ feature-rich supervised learning models which we extensively evalu- ate. We also showcase a crowd-supported workflow for building a suitable Gold dataset used for this purpo...