

Given a database of structures, an algorithm for mining structured data is
an algorithm that searches for interesting information in these structures. Examples of structures
are graphs, trees, molecules, XML documents and relational databases. At the moment this homepage concentrates on algorithms that search for descriptions of
structures. Descriptions may
be subgraphs, subtrees, `submolecules', etc., that satisfy constraints such
as minimum frequency, minimum confidence, minimum interest, maximum
frequency, etc. The
target of descriptive mining algorithms is not to find a predictive
model, but to find a good description of existing data in order to gain
insight into that data.

