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In this paper, the authors explore several computational models for incongruity resolution.
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11 p.
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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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Mihalcea, Rada, 1974-; Strapparava, Carlo, 1962- & Pulman, Stephen.Computational Models for Incongruity Detection in Humour,
paper,
March 2010;
(https://digital.library.unt.edu/ark:/67531/metadc31024/:
accessed April 19, 2025),
University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu;
crediting UNT College of Engineering.
