基于数据挖掘与业务感知的投诉预测模型研究

Research on complaint prediction model based on data mining and business awareness

随着网络智能化快速演进,用户投诉从被动处理转向主动维护,从人工维护转向加大网络自治自愈。针对当前现状与发展策略,本文提出基于数据挖掘与业务感知的投诉预测体系,以提升智能隐患主动监测能力。该体系通过分析用户行为和网络指标等,基于决策树和K-Means聚类分析等建立模型,对潜在投诉用户进行预测,形成完整的早于客户的投诉预测体系,能够有效地解决客户投诉数据分析的问题,主动发现问题,进而提出相应的优化方案,提升用户感知和体验。

As the network intelligent rapid evolution,from passive process to active maintenance,from artificial maintenance to increase network autonomous self-healing,therefore,in view of the current situation and development strategy is put forward based on data mining and business awareness of complaints prediction system,to enhance the intelligence hidden active monitoring ability,the system through the analysis of user behavior,network,etc.,Based on decision tree,K-Means cluster analysis and other modeling prediction,the potential complaint users are predicted,and the formation of a complete complaint prediction system earlier than customers can effectively solve the problem of customer complaint data analysis,proactively discover the problem,and then put forward the corresponding optimization scheme to improve user perception and experience.