基于深度神经网络的电子商务智能客服系统设计与实现

近年来,随着自然语言处理技术的飞速发展,传统的客服越来越不能满足当前的业务需求,基于自然语言技术的智能客服系统应运而生并被广泛应用在学习、生活、工作等各个领域中。本系统使用HTML和JavaScript进行前端页面的实现,采用Django进行后端的搭建,并使用MySQL进行数据的管理;使用ESIM模型进行语义匹配,该模型综合应用了BiLSTM和注意力机制,将不同句子的各单词特征相关性进行表示,再进行差积分析,凸显了局部推理信息,最终实现了具有回答用户问题、天气查询、推荐商品等功能的智能客服系统。

Design and Implementation of E-commerce Intelligent Customer Service System based on Deep Neural Network

In recent years,with rapid development of natural language processing technology,traditional customer service is increasingly unable to meet current business needs.Intelligent customer service system based on natural language technology has emerged and is widely used in various fields,such as study,life,and work.This paper proposes to design an E-commerce intelligent customer service system using HTML(HyperText Markup Language)and JavaScript to implement the front-end page,Django to build the back-end,MySQL(Structured Query Language)to manage data,and the ESIM(Enhanced Sequential Inference Model)to perform semantic matching.This model uses BiLSTM(Bidirectional Long Shortterm Memory)and attention mechanism to combine different sentences.Feature relevance of each word is expressed,and then difference product analysis is performed,which highlights the local reasoning information.Finally,the intelligent customer service system with functions such as answering user questions,weather inquiries,and recommending products is realized.