Yunxia Ding


2019

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YNU_DYX at SemEval-2019 Task 5: A Stacked BiGRU Model Based on Capsule Network in Detection of Hate
Yunxia Ding | Xiaobing Zhou | Xuejie Zhang
Proceedings of the 13th International Workshop on Semantic Evaluation

This paper describes our system designed for SemEval 2019 Task 5 “Shared Task on Multilingual Detection of Hate”.We only participate in subtask-A in English. To address this task, we present a stacked BiGRU model based on a capsule network system. In or- der to convert the tweets into corresponding vector representations and input them into the neural network, we use the fastText tools to get word representations. Then, the sentence representation is enriched by stacked Bidirectional Gated Recurrent Units (BiGRUs) and used as the input of capsule network. Our system achieves an average F1-score of 0.546 and ranks 3rd in the subtask-A in English.

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YNU_DYX at SemEval-2019 Task 9: A Stacked BiLSTM for Suggestion Mining Classification
Yunxia Ding | Xiaobing Zhou | Xuejie Zhang
Proceedings of the 13th International Workshop on Semantic Evaluation

In this paper we describe a deep-learning system that competed as SemEval 2019 Task 9-SubTask A: Suggestion Mining from Online Reviews and Forums. We use Word2Vec to learn the distributed representations from sentences. This system is composed of a Stacked Bidirectional Long-Short Memory Network (SBiLSTM) for enriching word representations before and after the sequence relationship with context. We perform an ensemble to improve the effectiveness of our model. Our official submission results achieve an F1-score 0.5659.