International Journal of Man-Machine Studies - Special Issue: Knowledge Acquisition for Knowledge-based Systems. Part 5
Automated knowledge acquisition
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Data mining and knowledge discovery in databases
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Spectral methods for detecting periodicity in library circulation data: a case study
Information Processing and Management: an International Journal
A new explanation of the geometric law in the case of library circulation data
Information Processing and Management: an International Journal
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Future Generation Computer Systems - Special double issue on data mining
Data mining for customer service support
Information and Management
Mining Multiple-Level Association Rules in Large Databases
IEEE Transactions on Knowledge and Data Engineering
Machine Learning
Knowledge discovery applied to material acquisitions for libraries
Information Processing and Management: an International Journal
Information Processing and Management: an International Journal
Information Processing and Management: an International Journal
An online book recommendation system based on web service
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 7
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Many approaches to decision support for the academic library acquisition budget allocation have been proposed to diversely reflect the management requirements. Different from these methods that focus mainly on either statistical analysis or goal programming, this paper introduces a model (ABAMDM, acquisition budget allocation model via data mining) that addresses the use of descriptive knowledge discovered in the historical circulation data explicitly to support allocating library acquisition budget. The major concern in this study is that the budget allocation should be able to reflect a requirement that the more a department makes use of its acquired materials in the present academic year, the more it can get budget for the coming year. The primary output of the ABAMDM used to derive weights of acquisition budget allocation contains two parts. One is the descriptive knowledge via utilization concentration and the other is the suitability via utilization connection for departments concerned. An applicat-ion to the library of Kun Shan University of Technology was described to demonstrate the introduced ABAMDM in practice.