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An evaluation model of e-commerce credit information based on social big data

An evaluation model of e-commerce credit information based on social big data To overcome the problems of low accuracy and poor stability in the evaluation of Internet trading activities, an evaluation model of e-commerce credit information based on social big data is proposed. The model will be composed of four layers: basic data layer, synthetic data layer, random model layer and integrated learning layer. The logical structure of the model is divided into social communication big data preprocessing, credit evaluation submodel establishment, evaluation submodel integration, so as to enhance the ability of the credit division model. On this basis, the credit evaluation index system is established, and the e-commerce credit information is evaluated by the BP neural network method. The results of model verification show that the model has good generalisation ability and accuracy, can distinguish important variables effectively and stably, can acquire the e-commerce credit situation more scientifically, and can control the security situation of e-commerce credit information in the social big data environment. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Autonomous and Adaptive Communications Systems Inderscience Publishers

An evaluation model of e-commerce credit information based on social big data

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd
ISSN
1754-8632
eISSN
1754-8640
DOI
10.1504/ijaacs.2022.127455
Publisher site
See Article on Publisher Site

Abstract

To overcome the problems of low accuracy and poor stability in the evaluation of Internet trading activities, an evaluation model of e-commerce credit information based on social big data is proposed. The model will be composed of four layers: basic data layer, synthetic data layer, random model layer and integrated learning layer. The logical structure of the model is divided into social communication big data preprocessing, credit evaluation submodel establishment, evaluation submodel integration, so as to enhance the ability of the credit division model. On this basis, the credit evaluation index system is established, and the e-commerce credit information is evaluated by the BP neural network method. The results of model verification show that the model has good generalisation ability and accuracy, can distinguish important variables effectively and stably, can acquire the e-commerce credit situation more scientifically, and can control the security situation of e-commerce credit information in the social big data environment.

Journal

International Journal of Autonomous and Adaptive Communications SystemsInderscience Publishers

Published: Jan 1, 2022

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