An efficient strategy for mining exceptions in multi-databases

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Journal Article
Information Sciences, 2004, 165 (1-2), pp. 1 - 20
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This paper proposes a new strategy, referred to as local instance analysis, for multi-database mining. While many interstate organizations have an imperative need to analyze their data in multi-databases distributed throughout their branches, traditional multi-database mining utilizes the strategies for mono-database mining: pooling all the data from relevant databases into a single dataset for discovery. This leads to the destruction of useful information, for instance, '70% of branches within a company agreed that a married customer usually has at least 2 cars if his/her age is between 45 and 65'. This information assists in global decision-making within the company. Our new strategy is developed for discovering this useful information. Using the local instance analysis, we design an algorithm for identifying exceptions from multi-databases. Exceptional pattern reflects the 'individuality' of, say, branches of an interstate company. © 2003 Elsevier Inc. All rights reserved.
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