@inproceedings{jensen-etal-2020-buhscitu,
title = "Buhscitu at {S}em{E}val-2020 Task 7: Assessing Humour in Edited News Headlines Using Hand-Crafted Features and Online Knowledge Bases",
author = "Jensen, Kristian N{\o}rgaard and
Rasmussen, Nicolaj Filrup and
Wang, Thai and
Placenti, Marco and
Plank, Barbara",
editor = "Herbelot, Aurelie and
Zhu, Xiaodan and
Palmer, Alexis and
Schneider, Nathan and
May, Jonathan and
Shutova, Ekaterina",
booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
month = dec,
year = "2020",
address = "Barcelona (online)",
publisher = "International Committee for Computational Linguistics",
url = "https://aclanthology.org/2020.semeval-1.104/",
doi = "10.18653/v1/2020.semeval-1.104",
pages = "824--832",
abstract = "This paper describes a system that aims at assessing humour intensity in edited news headlines as part of the 7th task of SemEval-2020 on {\textquotedblleft}Humor, Emphasis and Sentiment{\textquotedblright}. Various factors need to be accounted for in order to assess the funniness of an edited headline. We propose an architecture that uses hand-crafted features, knowledge bases and a language model to understand humour, and combines them in a regression model. Our system outperforms two baselines. In general, automatic humour assessment remains a difficult task."
}
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%0 Conference Proceedings
%T Buhscitu at SemEval-2020 Task 7: Assessing Humour in Edited News Headlines Using Hand-Crafted Features and Online Knowledge Bases
%A Jensen, Kristian Nørgaard
%A Rasmussen, Nicolaj Filrup
%A Wang, Thai
%A Placenti, Marco
%A Plank, Barbara
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y May, Jonathan
%Y Shutova, Ekaterina
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 December
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F jensen-etal-2020-buhscitu
%X This paper describes a system that aims at assessing humour intensity in edited news headlines as part of the 7th task of SemEval-2020 on “Humor, Emphasis and Sentiment”. Various factors need to be accounted for in order to assess the funniness of an edited headline. We propose an architecture that uses hand-crafted features, knowledge bases and a language model to understand humour, and combines them in a regression model. Our system outperforms two baselines. In general, automatic humour assessment remains a difficult task.
%R 10.18653/v1/2020.semeval-1.104
%U https://aclanthology.org/2020.semeval-1.104/
%U https://doi.org/10.18653/v1/2020.semeval-1.104
%P 824-832
Markdown (Informal)
[Buhscitu at SemEval-2020 Task 7: Assessing Humour in Edited News Headlines Using Hand-Crafted Features and Online Knowledge Bases](https://aclanthology.org/2020.semeval-1.104/) (Jensen et al., SemEval 2020)
ACL