Association Rule Of Borrowed Books

With the rapid development of modern society, update speed of knowledge and the closer relations between different subjects, the demand for knowledge to students is higher and higher. As a window connecting the outside with students and teachers, library in university is more and more important. It is not only convenient to consult literatures, but also is another place to acquire knowledge outside of the classroom for students. Now database technology is adopted to manage the library in almost every university, which is convenient for books purchase, catalogue and effective management of books circulation. In the circulation of books, a lot of data are produced, while the students'borrowing information is one of the most important data. Developmental direction and association extent of subjects are represented by the borrowing information of students to some extent, especially masters and doctors. The aim in this paper is to mine association rules among different subjects from lots of borrowing information.Firstly, application prospects of data mining at home and abroad are discussed. Subsequently, correlative theories of association rules are presented. Then data of borrowed books are preprocessed, which includes data-importing and data extraction, and transaction database is established. After that, association rules of borrowed books based on Apriori algorithm and FP-Growth algorithm are realized. According to the results, the meaning of the subject and comparison of two different algorithms are analyzed. Finally, conclusion and expectation are described.The results of mining association rule of borrowed books show that books about program language, books about network browser, books about Internet and books about image recognition are borrowed with high probability at the same time. The differences of runtime between Apriori algorithm and FP-Growth algorithm are educed. It is proposed that mining association rules of borrowed books will have bright prospects in university library.