摘要
采用基于正则表达式和Python编程的文本挖掘方法,提取了国网各省市供电公司95598投诉工作单中客户描述的停电次数和实际停电次数的处理意见,对数据进行了分析。结果表明,文本挖掘技术可以有效地应用于从95598投诉文档中提取出非结构化文本数据,当出现两次或两次以上的停电时,客户往往会抱怨更多。
The text mining method based on regular expression and Python programming are used to extract the number of power cuts described by customers and the actual number of power cuts in the handling opinions in the handling of 95598 complaint work orders of CNNM, and have carried out in-depth analysis. The results show that the text mining technology can be effectively applied to the extraction of unstructured text data from 95598 complaint documents. When there are two or more power outages, customers tend to complain more.
作者
万磊
严道波
杨勇
何镇庭
邱丹
吴迪
WAN Lei;YAN Daobo;YANG Yong;HE Zhenting;QIU Dan;WU Di(State Grid Hubei Electric Power Co.,Ltd.,Wuhan 430070,China;State Grid Hubei Electric Power Co.,Ltd.Ezhou Power Supply Company,Ezhou 436000,China)
出处
《电力与能源》
2019年第1期70-72,共3页
Power & Energy
关键词
供电企业
营销管理
用户数据分析
正则表达式
文本挖掘技术
power supply enterprises
marketing management
user data analysis
regular expressions
text mining technology
