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Abstract

For decades, the corporate sector has exploited technological advances to better market and deliver products and services to customers via the techniques of data mining. The technique was not widely used in libraries. However, with the current emphasis on evidence-based decision making, libraries are beginning to utilize their system- and user- generated data. Data mining usually involves a significant endeavor to extract embedded and potentially useful information from large undiscovered data sets (Mitra & Acharya, 2003; Hand, Mannila & Smyth, 2001; Frawley, Piatetsky-Shapiro, & Matheus 1992; Piatetsky-Shapiro & Frawley 1991).

These data mining techniques are being used by librarians to improve both internal decision-making and external user services by extracting information from operational datasets of both bibliographic and user data. OCLC Research has taken advantage of the WorldCat database, which includes more than 95 million bibliographic records and 1.2 billion holdings records, as well as data provided by other major library systems and consortia to develop user-oriented collections and services (http://www.oclc.org/research/projects/mining/).