Data mining applied to material acquisition budget allocation for libraries: design and development
Library management frequently faces the need of making the value of the acquired materials significant as far as the most beneficial use of the allocated acquisition budget is concerned. Knowledge in the circulation databases can be explored in-depth to relevantly reflect this need. In this paper, a data mining based model (DMBA) is designed and developed to help allocate the library material acquisition budget by opening up the utilization of library materials that users have made use. The developed model is based on the feature of ID3 algorithm to explore explanatory knowledge via information theory and statistics to derive appropriateness via utilization gain. The main output of the DMBA is the weights as the basis of library material acquisition budget allocation for departments via the combination of explored explanatory knowledge and appropriateness. The developed DMBA was supported by a practical application case.
data mining acquisition budget allocation circulation