In this paper we present our approach and the system description for Sub Task A of SemEval 2019 Task 9: Suggestion Mining from Online Reviews and Forums. Given a sentence, the task asks to predict whether the sentence consists of a suggestion or not. Our model is based on Universal Language Model Fine-tuning for Text Classification. We apply various pre-processing techniques before training the language and the classification model. We further provide detailed analysis of the results obtained using the trained model. Our team ranked 10th out of 34 participants, achieving an F1 score of 0.7011. We publicly share our implementation at https://github.com/isarth/SemEval9_MIDAS
翻译：本文介绍2019年SemEval任务9(在线审查和论坛的建议采矿)A分任务A的方法和系统说明。根据一句话,任务要求预测该句是否包含一个建议。我们的模式以通用语言文本分类的微调模式为基础。在培训语言和分类模式之前,我们应用了各种预处理技术。我们进一步详细分析使用经过培训的模式取得的结果。我们的团队在34名参与者中排名第10位,获得F1分0.7011。我们在https://github.com/isarth/SemEval9_MIDAS上公开分享我们的执行情况。
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