| Description: | This paper discusses computational models for incongruity resolution. 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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| Creator(s): | |
| Creation Date: | March 2010 |
| Partner(s): |
UNT College of Engineering
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| Collection(s): |
UNT Scholarly Works
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| Usage: |
Total Uses: 184
Past 30 days: 7
Yesterday: 0
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| Creator (Author): |
Mihalcea, Rada, 1974-
University of North Texas |
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| Creator (Author): |
Strapparava, Carlo, 1962-
Fondazione Bruno Kessler (FBK)-IRST |
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| Creator (Author): |
Pulman, Stephen
University of Oxford |
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| Original Creation Date: | March 2010 | |
| Description: | This paper discusses computational models for incongruity resolution. 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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| Degree: |
Department:
Computer Science and Engineering
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| Physical Description: |
11 p. |
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| Keyword(s): | incongruity resolutions | sentiment analysis | humor recognition | |
| Source: | Conference on Computational Linguistics and Intelligent Text Processing (CICLing), 2010, Iasi, Romania | |
| Contributor(s): |
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| Partner: |
UNT College of Engineering
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| Collection: |
UNT Scholarly Works
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| Resource Type: | Paper | |
| Format: | Text | |
| Rights: |
Access:
Public
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