作　　者： (李楠）;

机构地区： 兰州总医院医务部科研训练科,730000

出　　处： 《中国数字医学》 2017年第8期85-87,共3页

摘　　要： 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 ＂tuling12Y＇ 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.

关 键 词： 客户服务系统 医院 问答 自然语言处理