Reasoning about sets using redescription mining

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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 biolog...
Mohammed Javeed Zaki, Naren Ramakrishnan
Added 30 Nov 2009
Updated 30 Nov 2009
Type Conference
Year 2005
Where KDD
Authors Mohammed Javeed Zaki, Naren Ramakrishnan
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