Chenghao Huang


2020

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Ferryman at SemEval-2020 Task 7: Ensemble Model for Assessing Humor in Edited News Headlines
Weilong Chen | Jipeng Li | Chenghao Huang | Wei Bai | Yanru Zhang | Yan Wang
Proceedings of the Fourteenth Workshop on Semantic Evaluation

Natural language processing (NLP) has been applied to various fields including text classification and sentiment analysis. In the shared task of assessing the funniness of edited news headlines, which is a part of the SemEval 2020 competition, we preprocess datasets by replacing abbreviation, stemming words, then merge three models including Light Gradient Boosting Machine (LightGBM), Long Short-Term Memory (LSTM), and Bidirectional Encoder Representation from Transformer (BERT) by taking the average to perform the best. Our team Ferryman wins the 9th place in Sub-task 1 of Task 7 - Regression.

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MeisterMorxrc at SemEval-2020 Task 9: Fine-Tune Bert and Multitask Learning for Sentiment Analysis of Code-Mixed Tweets
Qi Wu | Peng Wang | Chenghao Huang
Proceedings of the Fourteenth Workshop on Semantic Evaluation

Natural language processing (NLP) has been applied to various fields including text classification and sentiment analysis. In the shared task of sentiment analysis of code-mixed tweets, which is a part of the SemEval-2020 competition, we preprocess datasets by replacing emoji and deleting uncommon characters and so on, and then fine-tune the Bidirectional Encoder Representation from Transformers(BERT) to perform the best. After exhausting top3 submissions, Our team MeisterMorxrc achieves an averaged F1 score of 0.730 in this task, and and our codalab username is MeisterMorxrc