Event Extraction via DMCNN in Open Domain Public Sentiment Information

• 作者: Le Sun Linteng Wang Xiaoguang Li Zhanghui Wang
• 来源期刊: 国际计算机前沿大会会议论文集
• 学科: 文学
• 关键词: Text processing Attention mechanism Syntax analysis Neural network
• 年，卷（期）: 2020,（2）
• 页码范围: 90-100
• 页数: 11页
• 分类号: H31

摘要

Event extraction(EE)is a difficult task in natural language processing(NLP).The target of EE is to obtain and present key information described in natural language in a structured form.Internet opinion,as an essential bearer of social information,is crucial.In order to help readers quickly get the main idea of news,a method of analyzing public sentiment information on the Internet and extracting events from news information is proposed.It enables users to quickly obtain information they need.An event extraction method was proposed based on Chinese language public opinion information,aiming at automatically classifying different types of public opinion events by using sentence-level features,and neural networks were applied to extract events.A sentence feature model was introduced to classify different types of public opinion events.To ensure the effective retention of text information in the calculation process,attention mechanism was added to the semantic information,and an effective public opinion event extractor was trained through CNN and LSTM networks.Experiments show that structured information can be extracted from unstructured text,and the purpose of obtaining public opinion event entities,event-entity relationships,and entity attribute information can be achieved.