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Research on Bibliographic Push Service of University Library Based on Data Mining

机译:基于数据挖掘的大学图书馆书目推送服务研究

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Data mining is carried out by using the borrowing records of readers in the existing library information system. The classification numbers and titles of books borrowed by readers are calculated by TF-IDF algorithm to represent the personalized features of readers. The titles of push books are segmented into bibliographic features by the function of word segmentation. According to the corresponding algorithm, the characteristics of readers and bibliographic features are screened and judged, and the selected books are personalized for readers. The experimental results show that the bibliographic push service model of university library based on data mining has a good application effect.
机译:通过使用现有图书馆信息系统中的读取器的借阅记录来执行数据挖掘。读者借用的书籍的分类号和标题由TF-IDF算法计算,以表示读者的个性化功能。推动书的标题被单词分割的功能分段为书目特征。根据相应的算法,筛选和判断读者和书目特征的特征,所选的书籍是读者个性化的。实验结果表明,基于数据挖掘的大学图书馆的书目推送服务模型具有良好的应用效果。

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