Application of Improved Association-rules Mining Algorithm in the Circulation of University Library
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Tingting Xia, Yingjun Liu
The rapid development of network technology has brought great influence to library circles, How to reposition and retain readers of Libraries in the new period has aroused the thinking of industry. The consensus view is that libraries need to tap the needs of users to promote reader reflux. This paper is based on data mining technology and association-rules mining technology, by using the improved Apriori algorithm to mine frequent item sets in transaction databases for circulating information in library automation system. Through data mining and analysis, we can grasp the interests and needs of readers, offer some meaningful and practical results for managers, and provide decision-making suggestions on book purchasing, subject construction and collection distribution. Based on data mining technology and association rule mining technology, taking circulation information in library automation system as a sample, this paper uses improved Apriori algorithm to mine frequent item sets in transaction database. Through data mining analysis, it can grasp interests and needs of readers, and provide decision-making suggestions for library purchase, subject construction and collection distribution.
Library, data mining, association-rules