The Application Of The Mining Method On Book Lending Behavior Patterns In Students’ Library Management System

Along with the increasing of library resources, it is hard for readers to findappropriate and useful books quickly and effectively. This paper tries to introduce the datamining technology to the Books Management System and use association analysis to minebook lending behavior patterns. Therefore, it can recommend books for readers and guidetheir lending behaviors.The Apriori algorithm is one of the most classic algorithm of association rulesmining.But when the iterative Apriori algorithm running layer by layer, each candidateitemsets need to scan the data sets to determine themselves whether to be frequent itemsets.A kind of jump forward and back filling algorithm has been put forward according to thedisadvantage. The improved algorithm reduced the times which is used to scan the datasets. Experiments show that the improved algorithm has improved the efficiency of theApriori algorithm.Secondly, the Boolean Matrix Apriori algorithm is used to do the parallel algorithmfor big data association rules mining which is based on cloud computing platform. TheMapReduce is used to process the Boolean Matrix blocks by blocks which is combinedwith Hadoop platform and the Apriori algorithm to calculate the local support count of thedata sets of each blocks,then frequent itemsets of big data sets are obtained by combiningand integration. Analysis shows that the Apriori algorithm is suitful for frequent itemsetsmining of big data.Finally, By the process of analyzing the Books Management System writed LINUXscripts and PLSQL stored procedures which completed the pretreatment of the dataextraction, cleaning and conversion. And the improved algorithm is used to finish themining work of the book lending behavior. At last, the book lending behavior modelbecomes visible which is based on Java Web technology, Hibernate framework and Flex framework.