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Extended Dualization: Application to Maximal Pattern Mining

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Extended Dualization: Application to Maximal Pattern Mining

Lhouari Nourine Limos, Clermont-Ferrand, France

Abstract. The hypergraph dualization is a crucial step in many applications in log- ics, databases, artficial intelligence and pattern mining, especially for hypergraphs or boolean lattices. The objective of this talk is to study polynomial reductions of the du- alization problem on arbitrary posets to the dualization problem on boolean lattices, for which output quasi-polynomial time algorithms exist.

The main application domain concerns pattern mining problems, i.e. the identification of maximal interesting patterns in database by asking membership queries (predicate) to a database.

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