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Published in:
2009 | OriginalPaper | Chapter
Frequent Itemset Mining in Multirelational Databases
Authors : Aída Jiménez, Fernando Berzal, Juan-Carlos Cubero
Published in: Foundations of Intelligent Systems
Publisher: Springer Berlin Heidelberg
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This paper proposes a new approach to mine multirelational databases. Our approach is based on the representation of a multirelational database as a set of trees. Tree mining techniques can then be applied to identify frequent patterns in this kind of databases. We propose two alternative schemes for representing a multirelational database as a set of trees. The frequent patterns that can be identified in such set of trees can be used as the basis for other multirelational data mining techniques, such as association rules, classification, or clustering.