Short Text Classification Model Based on Multi-Attention
Yunxiang Liu, Qi Xu · 2020
Short text classification plays an important role in NLP and its applications span a wide range of activities such as sentiment analysis, spam detection. Recently, attention mechanism is widely used in text classification task. Inspired by this, a text classification model based on multi-attention network(MAN) is proposed in this study, which perform well in extracting information related to text category. In our model, we combine the textual information based on multi-attention mechanism, which enables model to focus on global information of the sentence. We tested effectiveness of our model using several standard text classification datasets. Experiment told that our model achieved state-of-the-art results on all datasets.