Clustering Analysis of Borrowing Data of University Library based on K-means Algorithm
Silin Li · 2022 IEEE 2nd International Conference on Electronic Technology, Communication and Information (ICETCI) · 2022
With the continuous progress and development of data mining, the application of data mining technology has been involved in all aspects of people. The data mining of the borrowing data of university library can master the reading trend of readers on the whole, and make scientific prediction according to the trend, so as to improve the management level of university library and the reading atmosphere of readers, which is beneficial to the construction of library collection. In this paper, K-means algorithm is mainly used for clustering analysis of borrowing data, and the clustering characteristics of readers and books are analyzed, so as to provide more rigorous and scientific research methods and ideas for library service innovation and library department cooperation.