document: Reasoning about sets using redescription mining Redescription mining is a newly introduced data mining problem that seeks to find subsets of data that afford multiple definitions . It can be viewed as a generalization of association rule mining , from finding implications to equivalences ; as a form of conceptual clustering , where the goal is to identify clusters that afford dual characterizations ; and as a form of constructive induction , to build features based on given descriptors that mutually reinforce each other . In this paper , we present the use of redescription mining as an important tool to reason about a collection of sets , especially their overlaps , similarities , and differences . We outline algorithms to mine all minimal ( non-redundant ) redescriptions underlying a dataset using notions of minimal generators of closed itemsets . We also show the use of these algorithms in an interactive context , supporting constraint-based exploration and querying . Specifically , we showcase a bioinformatics application that empowers the biologist to define a vocabulary of sets underlying a domain of genes and to reason about these sets , yielding significant biological insight .
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