基于深度语义匹配模型的智能客服系统设计

Design of Intelligent Customer Service System Based on Deep Semantic Matching Model

为保证智能服务的及时性,最大程度提升用户对智能服务的满意度,设计基于深度语义匹配模型的智能客服系统。用户通过交互层智能终端发送服务请求,通过数据层分析请求内容并查询其历史请求记录;将分析结果和查询结果传输至功能层;同时利用卷积深度语义匹配模型完成语义增强和匹配,并生成应答对话,将应答结果呈现至交互层,实现服务的交互。测试结果表明:学习率的取值为0.4时,系统可在训练次数为300次时完成训练,损失值接近为0;能够依据用户发送的内容文本识别用户情绪,在实行情绪安抚的同时提供应答服务。

In order to ensure the timeliness of intelligent services and maximize users'satisfaction with intelligent services,an intelligent customer service system based on deep semantic matching model is designed.The user requests the history data through the user interaction layer and sends the request through the user interaction layer.Transmit the analysis results and query results to the function layer at the same time.At the same time,the convolution depth semantic matching model is used to complete semantic enhancement and matching,generate response dialogue,and present the response results to the interaction layer to realize the interaction of services.The test results show that when the learning rate is 0.4,the system can complete the training when the training time is 300,and the loss value is close to 0.It can identify the user's emotions according to the content text sent by the user,and provide response service while appeasing the emotion.