Using trees to mine multirelational databases

This paper proposes a new approach to mine multirelational databases. Our approach is based on the representation of multirelational databases as sets of trees, for which we propose two alternative representation schemes. Tree mining techniques can thus be applied as the basis for multirelational data mining techniques, such as multirelational classification or multirelational clustering. We analyze the differences between identifying induced and embedded tree patterns in the proposed tree-based representation schemes and we study the relationships among the sets of tree patterns that can be discovered in each case. This paper also describes how these frequent tree patterns can be used, for instance, to mine association rules in multirelational databases.

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