图书馆入馆行为数据分析及可视化

Data analysis and visualization of library entry behaviour

为了多维度分析和挖掘读者的入馆行为规律,为图书馆的高效运营提供思路,以上海大学图书馆为例,通过数据预处理、数据挖掘、结果分析等流程,对该图书馆近一年的入馆行为数据进行统计、聚类和可视化分析,得出读者入馆的多角度关系;利用该图书馆近10年的入馆统计数据,对入馆频次进行了预测。模型得到统计、聚类和预测的分析结果,并通过可视化方式呈现了规律。实验结果表明读者入馆行为存在周期性、趋势性等规律,对图书馆资源调配有借鉴意义。

In order to analyze and excavate the rules of readers'entering the library and provide ideas for the efficient operation of the library,the library of Shanghai University is taken as an example,through data preprocessing,data mining,result analysis and other processes,makes statistical,clustering and visual analysis of the library's entering behavior data in the past year,the multi angle relationship of readers'entering the library is obtained;uses the library according to the statistical data of entering the library in the past 10 years,the frequency of entering the library is predicted.The analysis results of statistics,clustering and prediction are obtained by the model,and the rules are presented by visualization.The experimental results show that there are periodic and trend rules in the behavior of readers entering the library,which can be used for reference for the allocation of library resources.