Towards Cross-fertilization Between Propositional Satisfiability and Data Mining

In this talk, we overview our contribution to data mining and more generally to the cross-fertilization between data mining and propositional satisfiability (http://www.cril.univ-artois.fr/decMining/). We will focus on two contributions. First, we show how propositional satisfiability can be used to model and solve problems in data mining. As an illustration, we present a SAT-based declarative approach for enumerating top-k (closed, frequent) itemsets in transactional databases. Secondly, we discuss the potential contribution of data mining to propositional satisfiability. In this context, we present a first application of data mining to compress Boolean formulas conjunctive normal form.

Speaker Details

Lakhdar Saïs is a Professor of Computer Science at CRIL – CNRS, Artois University. He obtained a Ph.D (“Doctorat”) in 1993 from the “Université de Provence” (Marseille) and an “Habilitation à Diriger des Recherches” from the “Université d’Artois” in 2000. In 1994, he joined the “IUT de Lens” as a lecturer (“Maitre de conférences”) at the beginning of the creation of the CRIL research center (“Centre de Recherche en Informatique de Lens”). Before his current position as a Professor at CRIL – Artois University, he spent one year as a professor at IRIT {Université Paul Sabatier } (Toulouse, France). He spent two years as a researcher at INRIA Lille and CNRS. He was the leader (from 2002 – 2013) of the inference and decision process group at CRIL – CNRS. He is currently the Delegate director of the CRIL laboratory. His research focuses on search and representation problems in Artificial Intelligence. He is especially interested in propositional satisfiability, quantified Boolean formula, constraint satisfaction and optimisation problems, knowledge representation and reasoning, data mining. For further details on his research activities visit the web site: http://www.cril.fr/~sais

Date:
Speakers:
Lakhdar Sais
Affiliation:
CRIL

    • Portrait of Jeff Running

      Jeff Running