Abstract
University libraries have always been regarded as the information service centers of universities. Teachers’ teaching and scientific research and students’ extracurricular reference services are inseparable from the library’s collection of literature resources. With the increasingly prominent personalized needs of readers, the service orientation of the libraries of the College of Economics in colleges and universities is gradually transforming from the traditional provision of the explicit information to the personalized services that actively mine the implicit data information in order to meet the needs of the readers. The emergence of the data mining technology has brought opportunities to the personalized services of libraries. Through the analysis of the massive data, we can find the potential relationship between data.
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References
Lai S (2016) Analysis of the association rules of circulation data in University Libraries – taking the Library of Guangdong Institute of Petroleum and Chemical Technology as an example. Inf Explor (02):122–123
Wu X (2017) Application of the association rule data mining in the reader decision-making procurement. Sci Technol Square (02):105–106
Zhang R, Zhang Y (2017) Research on the intelligent recommendation technology of electronic libraries based on the data mining algorithms. J Southwest China Normal Univ (Nat Sci Ed) (07):133–134
Li X (2018) Application of the strong association rule mining in the personalized push service of intelligent libraries. Inf Sci (04):124–125
Zhao Y (2018) Research on the differentiated services of university libraries based on the data mining to percept readers’ needs. Libr Work and Study (07):138–139
Qingyuan Z, Jianjian L (2015) Artificial neural network based grid computing of E-government scheduling for emergency management. Comput Syst Sci Eng 30(5):335–343
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Lu, L., Cao, L. (2019). Analysis of the Application and the Association Rule Mining in the Library and Data Management of College of Economics. In: Sugumaran, V., Xu, Z., P., S., Zhou, H. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. MMIA 2019. Advances in Intelligent Systems and Computing, vol 929. Springer, Cham. https://doi.org/10.1007/978-3-030-15740-1_32
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DOI: https://doi.org/10.1007/978-3-030-15740-1_32
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