目的:利用机器学习和自然语言处理等技术,实现医院客服系统从模板式应答向智能学习式转型.方法:对市面上常见的客服系统进行归纳分类,原理阐述、优劣辨析、需求汇总并理出框架.在此基础上,借助“图灵机器人”平台搭建智能客服系统环境,并完成测试.结果:基于机器学习、语义分析等技术为医院量身定制的智能客服系统,可实现全天候、全自动为患者提供精准的答案和智能化的服务.结论:医院作为一个专业性强、垂直分科多、人流密度大的公共服务场所,引入无人值守的智能客服系统,既能显著节约人工客服的工作量,更能满足业务需求,提升患者体验.%Objective:Using the technology of machine learning and natural language processing,the hospital customer service system can be transformed from template analysis style to intelligent learning.Methods:Summarized the classification,principle,advantages and disadvantages,needs of the customer service system.On the basis of the above,build the test environment by using "tuling123"platform and finish the test work.Results:The intelligent customer service system which tailored for hospital,can provide patients with accurate answers and intelligent service All-weather and automaticly.Conclusion:The hospital is a professional,vertical specialized Places of public service,the intervention of intelligent customer service system,can significantly save artificial customer service work,more can satisfy the needs of the business,improving patients experience.
展开▼
