朴素贝叶斯分类算法在提升电信客户满意度方面的研究应用  

Research and Application of Naive Bayesian Classification Algorithm in Improving Telecom Customer Satisfaction

作　　者：张聪慧[1] ZHANG Cong-hui(School of Information Science and Technology, East China Normal University, Shanghai 200241, China)

机构地区：[1]华东师范大学信息科学与技术学院,中国上海200241

出　　处：《科技视界》2019年第2期122-123,共2页Science & Technology Vision

摘　　要：针对电信客户数据量庞大的特点,采用基于python语言的朴素贝叶斯分类算法,对电信客户的投诉内容进行分类,以便在更短的时间内对客户的投诉意见作出有效的处理,从而提高客户的满意度。In view of the huge amount of data of telecom customers, the naive Bayesian classification algorithm based on Python language is adopted to classify the complaints of telecom customers, so as to effectively deal with the complaints of customers in a shorter time, thereby improving customer satisfaction.

关 键 词：贝叶斯分类 多项式模型 高斯模型 伯努利模型 

分 类 号：TP23[自动化与计算机技术—检测技术与自动化装置]