Event Recognition on Public Safety Events Using Deep Learning Models

Event recognition is an important part of event extraction task. This paper generates pre-trained Chinese word vectors from Baidu Encyclopedia, Wikipedia_zh, People's Daily News and Sogou News using word2vec tools. Then two typical deep learning models, BiLSTM-CRF and IDCNN-CRF, are constructed to recognize trigger words and event types. The experimental results show that: 1. The word vectors pre-trained from Sogou News benefit model training and prediction; 2.On Chinese Emergency Corpus, deep learning models are generally superior to machine learning models in event recognition task; 3. The IDCNN-CRF model achieves an optimal F1 value of 76.4% for trigger word recognition, which also has the best training efficiency compared with other methods.

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