Computational Models for Incongruity Detection in Humour

Description:

In this paper, the authors explore several computational models for incongruity resolution.

Creator(s):
Creation Date: March 2010
Partner(s):
UNT College of Engineering
Collection(s):
UNT Scholarly Works
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Total Uses: 317
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Creator (Author):
Mihalcea, Rada, 1974-

University of North Texas

Creator (Author):
Strapparava, Carlo, 1962-

Fondazione Bruno Kessler (FBK)-IRST

Creator (Author):
Pulman, Stephen

University of Oxford

Date(s):
  • Creation: March 2010
Description:

In this paper, the authors explore several computational models for incongruity resolution.

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Abstract: Incongruity resolution is one of the most widely accepted theories of humor, suggesting that humor is due to the mixing of two disparate interpretation frames in one statement. In this paper, the authors explore several computational models for incongruity resolution. The authors introduce a new data set, consisting of a series of 'set-ups' (preparations for a punch line), each of them followed by four possible coherent continuations out of which only one has a comic effect. Using this data set, the authors redefine the task as the automatic identification of the humorous punch line among all the plausible endings. The authors explore several measures of semantic relatedness, along with a number of joke-specific features, and try to understand their appropriateness as computational models for incongruity detection.

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11 p.

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Subject(s):
Keyword(s): incongruity resolutions | sentiment analysis | humor recognition
Source: Conference on Computational Linguistics and Intelligent Text Processing (CICLing), 2010, Iasi, Romania
Contributor(s):
Partner:
UNT College of Engineering
Collection:
UNT Scholarly Works
Identifier:
  • ARK: ark:/67531/metadc31024
Resource Type: Paper
Format: Text
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Access: Public