数据挖掘技术在信用信息分析中的应用分析

Analysis of application of data mining technology in credit information analysis

文章首先简要概述与数据挖掘技术相关内容,随后从分类、聚类两种数据挖掘应用较广的维度来开展研究,分别有神经网络、决策树法、层次方法、基于密度(或网络)方法等;剖析了数据挖掘技术应用于信用信息分析的问题,而后围绕问题内容,指出可从强化海量数据处理效果、快速提炼信息分析报告、提前预测未来发展趋势、积极融合智慧化服务平台等方面解决问题,以期为相关技术工作提供可靠参考。

Based on the reality,this paper briefly summarizes the related content of data mining technology and introduces this research.Then,the research is carried out from the two dimensions of classification and clustering,which are widely used in data mining,including neural network,decision tree method,hierarchical method,density(or network)based method and so on.This paper analyzes the problems of applying data mining technology to credit information analysis,and then,focusing on the content of the problems,emphasizes that the problems can be solved by strengthening the effect of massive data processing,quickly refining information analysis reports,predicting future development trends in advance,and actively integrating intelligent service platforms,in order to provide reliable reference for related technical work.