Computer Science ›› 2019, Vol. 46 ›› Issue (2): 1-10.doi: 10.11896/j.issn.1002-137X.2019.02.001

• Big Data & Data Science •     Next Articles

Big Data Analytics and Insights in Distribution Characteristics of Supply Chain Finance

LIU Ying   

  1. School of Management Science and Information Engineering,Jilin University of Finance and Economics,Changchun 130117,China
    Jilin Province Key Laboratory of Logistics Industry Economy and Intelligent Logistics,Changchun 130117,China
    Laboratory of Internet Finance,Jilin University of Finance and Economics,Changchun 130117,China
  • Received:2018-08-30 Online:2019-02-25 Published:2019-02-25

Abstract: The semi-structured,unstructured and massive supply chain finance data make the analysis method relatively complicated in large data environment.How to use the unique characteristics of large samples to improve classification performance is worth exploring for the research on large data samples.This paper analyzed the main factors,which affectthe classification model of credit risk based on the distribution characteristics of financial data in supply chain,proposed distribution characteristics of credit data after researching the relevant achievements over the years,including imbalance data,noise and outliers,nonlinear multidimensional and so on,and then discussed further solutions to mine the know-ledge of the massive financial data,which provides an effective theoretical basis for the construction of credit risk model.

Key words: Supply chain finance, Credit risk, Big data, Distribution characteristics, Imbalance data, Outliers, Multi-dimension

CLC Number: 

  • TP399
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