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Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part I

Research Article

Research on Data Optimization Method of Software Knowledge Base Operation and Maintenance Based on Cloud Computing

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  • @INPROCEEDINGS{10.1007/978-3-030-67871-5_21,
        author={Gang Qiu and Shi-han Zhang},
        title={Research on Data Optimization Method of Software Knowledge Base Operation and Maintenance Based on Cloud Computing},
        proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part I},
        proceedings_a={ADHIP},
        year={2021},
        month={2},
        keywords={Cloud computing Software Knowledge base Operation and maintenance data},
        doi={10.1007/978-3-030-67871-5_21}
    }
    
  • Gang Qiu
    Shi-han Zhang
    Year: 2021
    Research on Data Optimization Method of Software Knowledge Base Operation and Maintenance Based on Cloud Computing
    ADHIP
    Springer
    DOI: 10.1007/978-3-030-67871-5_21
Gang Qiu1, Shi-han Zhang2,*
  • 1: Department of Computer Engineering, Changji College
  • 2: Shenyang Institute of Technology
*Contact email: Zhangshihan1324@163.com

Abstract

To improve the accuracy of data matching in software knowledge base operation and maintenance, a data optimization method based on cloud computing is proposed. In order to achieve the goal of accurate detection, the steps of anomaly detection of software knowledge base operation and maintenance data are improved, and the optimization of software knowledge base operation and maintenance data is completed. Finally, the experiment proves that the matching accuracy of the software knowledge base operation and maintenance data optimization method based on cloud computing is significantly improved compared with the traditional operation and maintenance method.

Keywords
Cloud computing Software Knowledge base Operation and maintenance data
Published
2021-02-03
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-67871-5_21
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