基于深度学习的智慧航空物流综合服务智能问答方法

Intelligent Q&A Method for Intelligent Aviation Logistics Comprehensive Services Based on Deep Learning

由于传统的智能问答方法难以处理复杂的语义关系和上下文信息,导致问答效果不佳,为此,提出基于深度学习的智慧航空物流综合服务智能问答方法。该方法可收集并增强智慧航空物流综合服务问答语句文本数据,基于深度学习构建BiLSTM模型,输入增强处理后文本数据进行智能问答语句文本语义匹配,实现对智慧航空物流综合服务中问题的智能回答响应。结果表明,所提方法下的智慧航空物流综合服务智能问答结果的Hits@K值高达0.917,反映该方法的回答效果较好。

Due to the difficulty of traditional intelligent question answering methods in handling complex semantic relationships and contextual information,the effectiveness of question answering is poor.Therefore,a deep learning based intelligent question answering method for intelligent aviation logistics comprehensive services is proposed.This method can collect and enhance the text data of intelligent aviation logistics comprehensive service question and answer statements.Based on deep learning,a BiLSTM model is constructed,and the enhanced text data is input for intelligent question and answer statement text semantic matching,achieving intelligent response to questions in intelligent aviation logistics comprehensive services.The results indicate that the intelligent question answering results of the intelligent aviation logistics comprehensive service under the proposed method are Hits@K The value is as high as 0.917,indicating that the response effect of this method is good.