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Issue title: Special Section: Intelligent & fuzzy theory in engineering and science
Guest editors: Teresa Guarda, Isabel Lopes and Álvaro Rocha
Article type: Research Article
Affiliations: Keyi College of Zhejiang Sci-Tech University, Hangzhou, Zhejiang, China
Correspondence: [*] Corresponding author. Yanna Hu, Keyi College of Zhejiang Sci-Tech University, Hangzhou, Zhejiang, 311121, China. E-mail: hyn19820912@126.com.
Abstract: The innovative concept of cloud computing in service model and technology has brought profound changes to the work of the library. In order to further realize the goal of library information resource sharing, this paper proposes a clustering algorithm that effectively evaluates the resource sharing operation mechanism, and effectively combines resource sharing cloud service with cloud computing. Based on the analysis of the key technologies of library information resource sharing cloud service, the cloud computing model algorithm is proposed and constructed to design the cloud service sharing model, and the IaaS cloud computing platform and the cost utility of the underlying support platform of SaaS and PaaS are developed. The library information resource sharing cloud service system is designed, and the performance of the system is analyzed and verified through experiments. The experimental results show that the running time of the algorithm on the four data sets is more than 30 times faster than the traditional clustering algorithm, which indicates that the algorithm is very effective compared with the traditional clustering algorithm. The research provides effective technical support and theoretical reference for the realization of library information resource sharing cloud service.
Keywords: Cloud computing model, library information, resource sharing, cloud service
DOI: 10.3233/JIFS-179168
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 5, pp. 5867-5875, 2019
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