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.
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Acknowledgements
This work was supported by the Research Project on Teaching Reform of Ordinary Colleges and Universities in Xinjiang Uygur Autonomous Region: Changji College - ZTE ICT Applied Talents Training Mechanism Research Project (2017JG117), as well as the South Xinjiang Education Development Research Center Project: Research on Xinjiang Bilingual Basic Education Curriculum Resources (XJEDU070116C11), and the 2019 Xinjiang Uygur Autonomous Region Higher Education Scientific Research Project (XJEDU2019Y057, XJEDU2019Y049).
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© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Qiu, G., Zhang, Sh. (2021). Research on Data Optimization Method of Software Knowledge Base Operation and Maintenance Based on Cloud Computing. In: Liu, S., Xia, L. (eds) Advanced Hybrid Information Processing. ADHIP 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 347. Springer, Cham. https://doi.org/10.1007/978-3-030-67871-5_21
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DOI: https://doi.org/10.1007/978-3-030-67871-5_21
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