YNU DYX at SemEval-2019 task 9: A stacked BiLSTM model for suggestion mining classification

Abstract

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.