1999 | OriginalPaper | Chapter
Peculiarity Oriented Multi-database Mining
Authors : Ning Zhong, Y. Y. Yao, Setsuo Ohsuga
Published in: Principles of Data Mining and Knowledge Discovery
Publisher: Springer Berlin Heidelberg
Included in: Professional Book Archive
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The paper proposes a way of mining peculiarity rules from multiply statistical and transaction databases. We introduce the peculiarity rules as a new type of association rules, which can be discovered from a relatively small number of the peculiar data by searching the relevance among the peculiar data. We argue that the peculiarity rules represent a typically unexpected, interesting regularity hidden in statistical and transaction databases. We describe how to mine the peculiarity rules in the multi-database environment and how to use the RVER (Reverse Variant Entity-Relationship) model to represent the result of multi-database mining. Our approach is based on the database reverse engineering methodology and granular computing techniques.