摘要
为了充分挖掘非结构化数据蕴含的信息价值,文章介绍了基于自然语言处理的文本挖掘技术,从原理到实践进行了探究。以电信运营商移动网络客户的体验与口碑为导向,利用文本挖掘技术在互联网舆情分析和客服部门投诉工单分析等方面进行探索,给出了基于非结构化文本数据的信息分类与呈现的方法,从而更好地聚焦客户需求和网络问题,支撑网络维护与优化工作,提升客户满意度。
In order to fully explore the information value contained in unstructured data,this article introduces text mining technology based on natural language processing,and explores it from principle to practice.Guided by the experience and reputation of telecom operators’mobile network customers,text mining technology was used to explore internet public opinion analysis and customer service department complaint work order analysis.Information classification and presentation methods based on unstructured text data were proposed,which better focused on customer needs and network issues,supported network maintenance and optimization work,and improved customer satisfaction.
作者
关志广
程乔
Guan Zhiguang;Cheng Qiao(Nanning College for Vocational Technology,Nanning 530008,China)
出处
《无线互联科技》
2023年第5期117-119,共3页
Wireless Internet Technology
基金
广西高校中青年教师科研基础能力提升项目,项目名称:基于Android的电信运营商网络感知提升APP设计与实现,项目编号:2021KY1014。
