Modeling and Analysis of Book Borrowing Flow in University Library Based on Data Mining

Borrowing flow of library books in the university library is influenced by a variety of factors, and has certain chaos change specificity. In view of the low precision of the current library borrowing flow prediction model, this paper puts forward the prediction model of the borrowing flow for Library drawing books based on data mining. Chaos theory is introduced to analyze original data of library borrowing flow in university library and establish the learning sample of library borrowing flow modeling in university library, data mining technology is used to build the book borrowing flow of University Library. The simulation experiments are carried out to test book borrowing flow prediction model in university library compared with other models. The results show that the proposed model can describe the changing trend of library borrowing flow in university library, and the performance of library borrowing flow prediction in university library is better, which can provide valuable reference information for university library managers.