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

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.