Journal
PATTERN RECOGNITION LETTERS
Volume 29, Issue 1, Pages 59-71Publisher
ELSEVIER
DOI: 10.1016/j.patrec.2007.09.001
Keywords
exceptional association rule; heavy association rule; high-frequent association rule; local pattern analysis; multi-database mining; synthesis of patterns
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Many large organizations have multiple databases distributed over different branches. Number of such organizations is increasing over time. Thus, it is necessary to study data mining on multiple databases. In this paper the following contributions are made: Firstly, an extended model is proposed for synthesizing global patterns from local patterns in different databases. Secondly, the notion of heavy association rule in multiple databases is introduced, and an algorithm for synthesizing such association rules in multiple databases is thus proposed. Thirdly, the notion of exceptional association rule in multiple databases is introduced, and an extension is made to the proposed algorithm to notify whether a heavy association rule is high-frequent or exceptional. We present experimental results on three real datasets. Also, we make a comparative analysis between the proposed algorithm and existing algorithm. (C) 2007 Elsevier B.V. All rights reserved.
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