Borrowing Data Mining Based on Association Rules

This article based on the actual university library business needs, using association rules to mining analysis universities Library students borrow data. First the library history borrowing data pretreatment, including data cleaning, data integration, data transformation and transaction database construction, Then the association rules mining algorithm MFP-Miner algorithm is applied to the transaction database, mining the association rules of borrowing books, for borrowing books and books recommended services providing scientific data support, so as to enhance the service quality of library.