Mark Last

Senior Academic

Why “Dark Thoughts” aren't really Dark

A Novel Algorithm for Metaphor Identification

Dan Assaf, Yair Neuman, Yohai Cohen, Shlomo Argamon, Newton Howard, Mark Last, Ophir Frieder, Moshe Koppel

Distinguishing between literal and metaphorical language is a major challenge facing natural language processing. Heuristically, metaphors can be divided into three general types in which type III metaphors are those involving an adjective-noun relationship (e.g. 'dark humor'). This paper describes our approach for automatic identification of type III metaphors. We propose a new algorithm, the Concrete-Category Overlap (CCO) algorithm, that distinguishes between literal and metaphorical use of adjective-noun relationships and evaluate it on two data sets of adjective-noun phrases. Our results point to the superiority of the CCO algorithm to past and contemporary approaches in determining the presence and conceptual significance of metaphors, and provide a better understanding of the conditions under which each algorithm should be applied.

Publication language English
Pages 60-65
Publication status Published - 01.01.2013
Article Number 6609166

Keywords

computational intelligence
computational linguistics
metaphor
natural language processing

ASJC Scopus subject areas

Artificial Intelligence
Modeling and Simulation
Access to Document
10.1109/CCMB.2013.6609166
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Link to publication in Scopus