Knowledge discovery applied to material acquisitions for libraries

Abstract

Since the quality of a library is not in the number of materials that are available, but in the number of materials that are actually utilized, this is what a material acquisitions operation should be concerned with. In support of this goal, the library management has been paying increased attention to the value of the usage data in support of a variety of managerial decisions. Although many approaches and research reports have been extensively used to help library material acquisitions, the knowledge contained in circulation databases has hardly ever been used to investigate in-depth how the acquired materials are being used. Thus, there may not be adequate indications on which the material acquisitions operation can rely when making decisions. This paper introduces a model based on knowledge discovery (KDBM LMA) that embeds a circulation statistics mechanism and an association rule discovery mechanism to help derive the utilization of library material categories. A practical application case is presented and managerial implications discussed in this research.