Min Wang


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Yuan at SemEval-2018 Task 1: Tweets Emotion Intensity Prediction using Ensemble Recurrent Neural Network
Min Wang | Xiaobing Zhou
Proceedings of The 12th International Workshop on Semantic Evaluation

We perform the LSTM and BiLSTM model for the emotion intensity prediction. We only join the third subtask in Task 1:Affect in Tweets. Our system rank 6th among all the teams.


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YNUDLG at IJCNLP-2017 Task 5: A CNN-LSTM Model with Attention for Multi-choice Question Answering in Examinations
Min Wang | Qingxun Liu | Peng Ding | Yongbin Li | Xiaobing Zhou
Proceedings of the IJCNLP 2017, Shared Tasks

In this paper, we perform convolutional neural networks (CNN) to learn the joint representations of question-answer pairs first, then use the joint representations as the inputs of the long short-term memory (LSTM) with attention to learn the answer sequence of a question for labeling the matching quality of each answer. We also incorporating external knowledge by training Word2Vec on Flashcards data, thus we get more compact embedding. Experimental results show that our method achieves better or comparable performance compared with the baseline system. The proposed approach achieves the accuracy of 0.39, 0.42 in English valid set, test set, respectively.