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WUY at SemEval-2020 Task 7: Combining BERT and Naive Bayes-SVM for Humor Assessment in Edited News Headlines
2020
Proceedings of the Fourteenth Workshop on Semantic Evaluation
unpublished
This paper describes our participation in SemEval 2020 Task 7 on assessment of humor in edited news headlines, which includes two subtasks, estimating the humor of micro-editd news headlines (subtask A) and predicting the more humorous of the two edited headlines (subtask B). To address these tasks, we propose two systems. The first system adopts a regression-based fine-tuned single-sequence bidirectional encoder representations from transformers (BERT) model with easy data augmentation (EDA),
doi:10.18653/v1/2020.semeval-1.141
fatcat:6fwncpjlyzgc3g3jn2pnfpmzkm