基于时间序列算法的高校图书馆借阅数据预测及分析  

Prediction and Analysis of Borrowing Bata in University Library Based on Time Series Algorithm

作　　者：李蛟 孟志强 LI Jiao;MENG Zhi-qiang(Library of Jinlin University,Changchun 130012,China)

机构地区：[1]吉林大学图书馆,吉林长春130012

出　　处：《情报科学》2022年第11期133-138,147,共7页Information Science

基　　金：吉林省社科基金项目“基于语义的高校图书馆数字资源聚合研究”(2019wt39);吉林大学基本科研业务费哲学社会科学研究种子基金项目“广度关联与深度语义融合的数字图书馆资源聚合服务质量评价与提升策略研究”(2017ZZ026)。

摘　　要：【目的/意义】图书借阅数据的预测对于图书馆的资源建设和精准服务具有重要的指导意义。本文收集了中国东北地区某双一流高校图书馆管理系统十年的借阅数据,并分别按图书类别、借阅者所属学院分类,对未来的借阅趋势进行了预测。【方法/过程】本文使用一种基于时间序列的混合预测模型进行图书借阅数量的预测,其中混合预测是一元时间序列预测与多元时间序列预测的结合。【结果/结论】实验结果表明,时间序列算法用于高校图书馆借阅数据预测,2008年到2017年借书数量由300左右增加到近4000,2018年到2021年C、D、G、J、S、U、I类图书中,D类、S类图书的借阅数量下降幅度最大,U类图书借阅数量下降幅度最小,T类、E类借阅量的上升幅度最大,Q类、X类的误差率较大,研究结论供高校图书馆管理工作参考。【创新/局限】学界上针对图书馆馆藏资源建设和服务创新研究较多,但以一元时间序列与多元时间序列预测角度进行研究的相对较少,本文弥补了此方面的不足。【Purpose/significance】The prediction of book borrowing data has an important guiding significance for library resource construction and accurate service.This paper collects the ten years’borrowing data of the library management system of a double firstclass university in Northeast China,and forecasts the borrowing trend in the future according to the categories of books and the colleges to which the borrower belongs.【Method/process】This paper uses a hybrid prediction model based on time series to predict the number of books borrowed,in which the hybrid prediction is the combination of monistic time series prediction and multivariate time series prediction.【Results/conclusion】The experimental results show that the time series algorithm is used to predict the borrowing data of university libraries.From 2008 to 2017,the number of books borrowed has increased from about 300 to nearly 4000.From2018 to 2021,the number of books borrowed by category D and S has decreased the most,the number of books borrowed by category U has decreased the least,the number of books borrowed by category T and E has increased the most,and the error rate of category Q and X is large,The research conclusion can be used as a reference for the management of university libraries.【Innovation/limitation】There are many researches on the construction of library collection resources and service innovation in the academic circle,but there are relatively few researches from the perspective of monistic time series and multivariate time series prediction.This paper makes up for the deficiencies in this regard.

关 键 词：图书馆 借阅数据 数据管理 时间序列 数据预测 

分 类 号：G258.6[文化科学—图书馆学]