Credibility Evaluation of Web Big Data Information Based on Particle Swarm Optimization

Authors

  • Nannan Zhao School of Computer Science and Engineering, Guangdong Ocean University at Yangjiang, China

DOI:

https://doi.org/10.13052/jwe1540-9589.21212

Keywords:

Credibility evaluation; Web big data; Improved particle swarm algorithm

Abstract

In order to improve the credibility evaluation effectiveness of web big data information, the improved particle swarm optimization is established. Firstly, framework of web big data is designed to include web big data source, data storage, data processing and data analysis. The global credibility calculation formula of whole web is established. Secondly, the improved particle swarm algorithm is constructed through updating weight and training factor, introducing cross and mutation operations into the algorithm, and improving population diversification based on mountain climbing algorithm. Finally, ten sample industries and one hundred sample stocks are selected to carry out experiment analysis, and the results show that the proposed algorithm can effectively distinguish trusted and untrustworthy records. And the proposed algorithm of calculating credibility of web big data has high reasonableness.

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Author Biography

Nannan Zhao, School of Computer Science and Engineering, Guangdong Ocean University at Yangjiang, China

Nannan Zhao received her B.Sc. and M.E. degrees in Computer Application Technology from Liaoning Technical University, China. She was awarded the title of Outstanding Teacher of Private Education in Guangdong Province. She won the Award of Guangdong Excellent Online Teaching Case, the special prize of university-level teaching Achievement Award, the Excellence Award of the 4th Guangdong Provincial College (undergraduate) Young Teachers’ Teaching Competition, the third prize of micro class of higher Education Group in Guangdong Provincial Computer Education Software Evaluation Activity, and the third prize of scientific research project of Guangdong Provincial Finance Department. She has been an excellent member of Jiusan Society in Zhanjiang City from 2019.

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Published

2022-01-17

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Articles