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Abstract

Traditional library catalogs have become inefficient and inconvenient in assisting library users. Readers may
spend a lot of time searching library materials via printed catalogs. Readers need an intelligent and innovative
solution to overcome this problem. The paper seeks to examine data mining technology, which is a good
approach to fulfill readers’ requirements. The purpose of this paper is to suggest the use of data mining (DM) as
a technique to support the process of redesigning a business by extracting the much-needed knowledge hidden
in large volumes of data maintained by the organization through the DM models. Data mining is considered the
non-trivial extraction of implicit, previously unknown, and potentially useful information from data. This paper
analyzes readers’ borrowing records using the techniques of data analysis, building a data warehouse, and data
mining. The paper finds that after mining data, readers can be classified into different groups according to the
publications in which they are interested. The data mining results shows that all readers can be categorized into
three clusters; each cluster has its own characteristics. This phenomenon shows that these readers have a
higher preference for accepting digitized publications.

Keywords: Digital-libraries, Data-mining, Data-warehouse

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