Borrowing patterns monitoring in Library: Application of Apriori algorithm

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dc.contributor.authorAdewole, K. S.
dc.contributor.authorAkintola, A. G.
dc.contributor.authorMabayoje, M. A.
dc.contributor.authorOgbomon, G. A.
dc.date.accessioned2017-11-23T13:59:29Z
dc.date.available2017-11-23T13:59:29Z
dc.date.issued2015
dc.description.abstractData is a valuable tool for any institution, and with the world advancing in technology, data stored in database management systems are growing in different capacities in almost all organization. The opportunities of database management systems have been explored. However, many organizations have not been able to leverage these opportunities in gaining business intelligence from their repositories. This paper addresses the issue of knowledge discovery from large databases using association rule mining. Apriori algorithm is implemented to discover hidden knowledge from a library database. Data depicting nine (9) different books were used within forty-seven (47) unique transactions. Eighteen (18) unique transactions were generated from the database showing the borrowing pattern of library users. The frequencies of borrowing of books were obtained as well as the associations. The result shows that borrowing a particular book may leads to borrowing another book as revealed in the association between Data structure in C (DS) textbook and Programming in C (C) textbook. The discovered pattern can help librarians in restructuring their bookshelf arrangement, and for book recommendation system. This system can also help students to have good knowledge different related books.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/17
dc.language.isoenen_US
dc.publisherInternational Journal of Information Processing and Communicationen_US
dc.subjectData Mining; Association Rule; Market Basket; Apriori Algorithm; Mining Support; Confidenceen_US
dc.titleBorrowing patterns monitoring in Library: Application of Apriori algorithmen_US
dc.typeArticleen_US

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