Borrowing Data Mining Based on Association Rules

Author

Long, Xiaojian ; Wu, Yuchun

Author_Institution

Sch. of Continuing Educ., Jinggangshan Univ., Ji´´an, China

Volume

2

fYear

2012

fDate

23-25 March 2012

Firstpage

239

Lastpage

242

Abstract

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.

Keywords

academic libraries; data mining; library automation; quality of service; transaction processing; MFP-miner algorithm; association rules mining algorithm; books recommended services; borrowing books; borrowing data mining; data cleaning; data integration; data transformation; library history borrowing data pretreatment; library service quality; scientific data support; transaction database construction; university library business needs; university library students borrow data mining analysis; Algorithm design and analysis; Association rules; Educational institutions; Itemsets; Libraries; MFP-Miner algorithm; association rule; data mining;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on

Conference_Location

Hangzhou

Print_ISBN

978-1-4673-0689-8

Type

conf

DOI

10.1109/ICCSEE.2012.179

Filename

6188010