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2020 SemEval SemEval 2020

YNU-HPCC at SemEval-2020 Task 7: Using an Ensemble BiGRU Model to Evaluate the Humor of Edited News Titles

Abstract

AbstractThis paper describes an ensemble model designed for Semeval-2020 Task 7. The task is based on the Humicroedit dataset that is comprised of news titles and one-word substitutions designed to make them humorous. We use BERT, FastText, Elmo, and Word2Vec to encode these titles then pass them to a bidirectional gated recurrent unit (BiGRU) with attention. Finally, we used XGBoost on the concatenation of the results of the different models to make predictions.

Authors

Joseph Tomasulo, Jin Wang, Xuejie Zhang

Topics

Machine Learning > Core Methods > Classification Machine Learning > Core Methods > Representation Learning Machine Learning > Learning Types > Self-Supervised Learning Machine Learning > Optimization & Theory > Neural Network Optimization

Keywords

ensemble learning text classification attention mechanism humor detection bidirectional gated recurrent unit
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