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- W3186649904 abstract "This paper describes the approach that was developed for SemEval 2021 Task 7 (Hahackathon: Incorporating Demographic Factors into Shared Humor Tasks) by the DUTH Team. We used and compared a variety of preprocessing techniques, vectorization methods, and numerous conventional machine learning algorithms, in order to construct classification and regression models for the given tasks. We used majority voting to combine the models’ outputs with small Neural Networks (NN) for classification tasks and their mean for regression for improving our system’s performance. While these methods proved weaker than modern, deep learning models, they are still relevant in research tasks because of their low requirements on computational power and faster training." @default.
- W3186649904 created "2021-08-02" @default.
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- W3186649904 date "2021-01-01" @default.
- W3186649904 modified "2023-09-26" @default.
- W3186649904 title "DUTH at SemEval-2021 Task 7: Is Conventional Machine Learning for Humorous and Offensive Tasks enough in 2021?" @default.
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- W3186649904 doi "https://doi.org/10.18653/v1/2021.semeval-1.157" @default.
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