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基于BiLSTM-CRF的社会突发事件研判方法

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社会突发事件的分类和等级研判作为应急处置中的一环,其重要性不言而喻。然而,目前研究多数采用人工或规则的方法识别证据进行研判,由于社会突发事件的构成的复杂性和语言描述的灵活性,这对于研判证据识别有很大局限性。本文参考"事件抽取"思想,事件类型和研判证据作为事件中元素,以BiLSTM-CRF方法细粒度的识别,并将二者结合,分类结果作为等级研判的输入,识别出研判证据。最终将识别结果结合注意力机制进行等级研判,通过对研判证据的精准识别从而来增强等级研判的准确性。实验表明,相比人工或规则识别研判证据,本文提出的方法有着更好的鲁棒性,社会突发事件研判时也达到了较好的效果。
基于BiLSTM-CRF的社会突发事件研判方法
In recent years,classification and rating of social emergency event have attracted more and more attentions in emergency management.However,most of the current studies adopt the rule-based methods to identify the evidences for event judgement,and have troubles in event judgement due to the complexity of social emergency event composition and the flexibility of language description.Inspired by the idea of event extraction,this paper has proposed the event judgement method via BiLSTM(Bidirectional Long-Short Term Memory)and CRF(Conditional Radom Fields)based on event classification and evidence extraction.The social emergency event classification is carried out firstly,and then the event evidences are extracted based on event type.In the end,the rating of social emergency event is judged with the attention mechanism and the combination of event type and evidence.Experimental results show that the proposed method is more robust than rule-based ones,and effective in the social emergency event judgement.

事件分类研判证据识别等级研判BiLSTM-CRF

胡慧君、王聪、代建华、刘茂福

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武汉科技大学计算机科学与技术学院,武汉,430065, 智能信息处理与实时工业系统湖北省重点实验室,武汉,430065

智能计算与语言信息处理湖南省重点实验室,湖南师范大学,长沙,410081

事件分类 研判证据识别 等级研判 BiLSTM-CRF

Chinese National Conference on Computational Linguistic

Haikou(CN)

19th Chinese National Conference on Computational Linguistic

667-675

2020