Metaphor Detection

Author

Cirstea, Bogdan-Ionut ; Chiru, Costin-Gabriel

Author_Institution

Dept. of Math., ENS Cachan, Cachan, France

fYear

2013

fDate

29-31 May 2013

Firstpage

210

Lastpage

217

Abstract

Because of the ubiquity of metaphors in language, metaphor processing is a very important task in the field of natural language processing. The first step towards metaphor processing, and probably the most difficult one, is metaphor detection. In the first part of this paper, we review the theoretical background for metaphors and the models and implementations that have been proposed for their detection. We then build corpora for detecting three types of metaphors: IS-A metaphors, metaphors formed with the preposition `of´ and metaphors formed with a verb. For the first two tasks, we train supervised classifiers using semantic features. For the third task, we use features commonly used in text categorization.

Keywords

natural language processing; pattern classification; text analysis; IS-A metaphors; metaphor detection; metaphor processing; natural language processing; preposition of metaphor; semantic features; supervised classifier training; text categorization; verb metaphor; Accuracy; Feature extraction; Google; Knowledge based systems; Semantics; Text categorization; Training; concreteness measures; figurative language; metaphor detection; similarity measures; supervised learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Systems and Computer Science (CSCS), 2013 19th International Conference on

Conference_Location

Bucharest

Print_ISBN

978-1-4673-6140-8

Type

conf

DOI

10.1109/CSCS.2013.74

Filename

6569267