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Data Mining of University Library Management Based on Improved Collaborative Filtering Association Rules Algorithm

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Abstract

To find out the hidden valuable information or some association rules of a large amount of information in current library books management system is of great guiding significance for the library management and service. In this paper, the collaborative filtering mining design was conducted for the university library management. Besides, library data mining was completed based on collaborative filtering algorithms, and the book recommendation model was generated. The test results showed that prediction success rate (precision ratio) of books based on collaborative filtering algorithm was much higher than that through the traditional algorithm. Therefore, the algorithm designed in this paper achieves the purpose and can be used for reference in university library management.

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Authors and Affiliations

  1. Library, Tourism College of Zhejiang, Hangzhou, China

    Yangdi Liu

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  1. Yangdi Liu
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Correspondence to Yangdi Liu.

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Liu, Y. Data Mining of University Library Management Based on Improved Collaborative Filtering Association Rules Algorithm. Wireless Pers Commun 102, 3781–3790 (2018). https://doi.org/10.1007/s11277-018-5409-y

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  • DOI: https://doi.org/10.1007/s11277-018-5409-y

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