Analysis Of Library Borrowing Behavior Based On Data Mining

As a knowledge sharing platform, libraries have a significant impact on readers. In this paper, data mining method is adopted to analyze the library circulation data, the result of which is to be used in library management decisions so as to raise the level of library services.The research is to be carried out in the following three aspects:Firstly, make statistical descriptions on book lending time, departments and grades to show the characteristics of these three attributes and then use the result to help with the library management decisions.Secondly, establish a new kind of clustering algorithm based on matrix data to accurately divide readers into different groups and figure out the group lending behavior characteristics.On one hand, it gives feedback to readers to help them form study groups and exchange ideas;on the other hand, it can be used for the personalized recommendation and the improvement of library service level.Thirdly, use Apriori algorithm to make association analysis on the books lended to figure out the incidence relation of the books and the strong association rules. The conclusion can be used to help with the book layout and personalized recommendation and optimize the library service quality.