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Application of Big Data Analysis in Personalized Service Management of University Libraries

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DOI: 10.23977/infkm.2023.040109 | Downloads: 23 | Views: 736


Mingde He 1


1 Shandong Jiaotong Vocational College, Weifang, Shandong, 261206, China

Corresponding Author

Mingde He


Big data (BD) is currently the most popular technology. Information technology based on BD has become a new technology that can support large-scale data processing. Its application scope is mainly in the comprehensive processing of large-scale information, and those university libraries that need large-scale data processing do need corresponding technical support. Especially in efficient libraries, because it involves tens of thousands of books of college teachers and students, in the current situation, traditional library management methods are increasingly unable to adapt to the impact of massive data. Therefore, in the management of libraries, the introduction of BD technology can improve the management efficiency of libraries, thereby providing better services to more students and students. This paper first introduced the basic framework of BD. Then, BD was applied to personalized service management in university libraries, which improved the overall efficiency. Finally, the questionnaire used to survey library staff and library customers could indicate that people had a high demand for personalized services. Therefore, making good use of BD for personalized service management in university libraries is a very worthy research topic.


Big Data, Library Management, Personalized Service, Data Analysis Algorithm


Mingde He, Application of Big Data Analysis in Personalized Service Management of University Libraries. Information and Knowledge Management (2023) Vol. 4: 71-78. DOI:


[1] Pisareva O M. Analysis of the State and Characteristics of the Development Potential of Strategic Planning Tools in the Digital Transformation Conditions of the Economy and Management. MIR (Modernization Innovation Research), 2019, 9(4):502-529. 
[2] Zhang F, Liu Q H. Innovation of Geography by Artificial Intelligence _Big Data_Cloud Computing. Journal of Global Change Data & Discovery, 2018, 2(3):362-365.
[3] Clim A, Zota R D, Tinica G. Big Data in home healthcare: A new frontier in personalized medicine. Medical emergency services and prediction of hypertension risks. International Journal of Healthcare Management, 2019, 12(3):241-249.
[4] Manikyam N, Kumar S M. Methods and techniques to deal with big data analytics and challenges in cloud computing environment. International Journal of Civil Engineering and Technology, 2017, 8(4):669-678.
[5] Lv X, Li M. Application and Research of the Intelligent Management System Based on Internet of Things Technology in the Era of Big Data. Mobile Information Systems, 2021, 2021(16):1-6.
[6] Qi S. Approaches to Information Service and Management Construction in University Libraries. International Journal of Social Science and Education Research, 2019, 2(5):41-45
[7] Sirhan A A, Abdrabbo K M, Tawalbeh S, et al. Digital rights management (DRM) in libraries of public universities in Jordan. Library management, 2019, 40(8/9):496-502.
[8] Novikov S V. Data Science and Big Data Technologies Role in the Digital Economy. TEM Journal, 2020, 9(2):756-762.
[9] Bai X, Li J. Personalized dynamic evaluation technology of online education quality management based on artificial intelligence big data. Journal of Intelligent and Fuzzy Systems, 2021(3):1-10.
[10] Savitskaya T E. New Library Services in the Framework of Digital Humanities Projects: Foreign Experience. Bibliotekovedenie [Russian Journal of Library Science], 2021, 70(1):55-64.
[11] Laterza V. Could Cambridge Analytica Have Delivered Donald Trump's 2016 Presidential Victory? An Anthropologist's Look at Big Data and Political Campaigning. Public Anthropologist, 2021, 3(1):119-147.
[12] Qin J, Zhou Z, Tan Y. A Big Data Text Coverless Information Hiding Based on Topic Distribution and TF-IDF. International Journal of Digital Crime and Forensics, 2021, 13(4):40-56.
[13] Kazakova N, Mel'Nik M, Dudorova E. Prospects for Implementing Big Data Analytics into the Auditing Profession. Auditor, 2021, 7(3):40-47.
[14] Xie C, Gui Y, Wong C S. Converting Double-Stranded DNA-Encoded Libraries (DELs) to Single-Stranded Libraries for More Versatile Selections. ACS Omega, 2022, 7(13):11491-11500.
[15] Hohnen P, Ulfstjerne M A, Krabbe M S. Assessing Creditworthiness in the Age of Big Data: A Comparative Study of Credit Score Systems in Denmark and the US. Journal of Extreme Anthropology, 2021, 5(1):29-55.
[16] Deng Y. Construction of higher education knowledge map in university libraries based on MOOC. The Electronic Library, 2019, 37(5):811-829.
[17] Ye P, Liu L, Gao L. Influence of Information and Service Quality on Users' Continuous Use of Mobile Libraries in China. Journal of Cases on Information Technology, 2020, 22(1):57-71.
[18] Savitskaya T E. New Library Services in the Framework of Digital Humanities Projects: Foreign Experience. Bibliotekovedenie [Russian Journal of Library Science], 2021, 70(1):55-64.
[19] Prakash P, Singh M P. Disaster Management Strategies of the Central University Libraries in Uttar Pradesh, India: A Study. GeroFam-A peer reviewed evidence-based gerontology-oriented family practice journal, 2021, 10(40):147-152.
[20] WenjinZHANG, ZhongyuQIN, ZhaoFENG. Big data analysis for detection of web brute-force attack. Journal of Shenzhen University Science and Engineering, 2020, 37(Z1):44-49.

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