大数据背景下的互联网融资信用评价体系构建

Construction of Internet Financing Credit Evaluation System under the Background of Big Data

互联网融资平台为小微企业提供融资新途径,但由于对小微企业征信体系建设知识的匮乏,造成互联网融资平台资金供应链断裂,损害多方利益,引发平台信用危机。该文立足于大数据分析环境,即以小微企业互联网融资流程为基础,分析所涉及的人、物、事及它们之间的关系,并以这些主体作为中心概念点扩展数据收集的范畴;构建企业本体,在全局概念的基础上利用层次聚类算法、关联规则挖掘算法、统计学及概念相似度分析方法,获取小微企业互联网融资大数据中的信用评价指标概念及概念间关系,并计算概念权重,构建信用评价指标体系。搭建Python 3.0仿真实验环境,经验证,利用该文所提算法在对概念抽取的精准度上要高于普通文本挖掘算法,但算法运行中复杂度较高,分析耗费的时间效率较低。

Internet financing platform provides a new way of financing to small and micro enterprises.Due to the lack of knowledge of the construction of credit information system onsmall and micro enterprises,which resultsin the break of internet financing platform capital supply chain,damages the interests of many parties,and triggersthe credit crisis of the platform.Based on the bigdata analysis environment,and the internet financing process of small and micro enterprises,this paper analyzes the people,things and matters involved and the relationship between them,and uses these subjects as the central concept to expand the scope of data collection.Based on the enterprises＇ ontology,this paper uses the hierarchical clustering algorithm,association rule mining algorithm,statistics and the concept similarity analysis to obtain the concept of credit evaluation index and the relationship between concepts from the large data of internet financing of small and micro enterprises,to calculate the weight of concept,and to build credit evaluation index system.By building Python 3.0 simulation experiment environment,and by experts＇ verification,the algorithm proposed inthis paper,in terms of the precision of concept extraction,is higher than that of the ordinary text mining algorithm.The algorithm is more efficient in the operation,but the time efficiency consumed by analysis is low.