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Communication Dans Un Congrès Année : 2018

A parallel SAT-based framework for closed frequent itemsets mining

Résumé

Constraint programming (CP) and propositional satisfiabil- ity (SAT) based framework for modeling and solving pattern mining tasks has gained a considerable audience in recent years. However, this nice declarative and generic framework encounters a scaling problem. The huge size of constraints networks/propositional formulas encoding large datasets is identified as the main bottleneck of most existing ap- proaches. In this paper, we propose a parallel SAT based framework for itemset mining problem to push forward the solving efficiency. The pro- posed approach is based on a divide-and-conquer paradigm, where the transaction database is partitioned using item-based guiding paths. Such decomposition allows us to derive smaller and independent Boolean for- mulas that can be solved in parallel. The performance and scalability of the proposed algorithm are evaluated through extensive experiments on several datasets. We demonstrate that our partition-based parallel SAT approach outperforms other CP approaches even in the sequential case, while significantly reducing the performances gap with specialized approaches
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Dates et versions

hal-01895369 , version 1 (15-10-2018)

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Citer

Imen Ouled Dlala, Saïd Jabbour, Badran Raddaoui, Lakhdar Saïs. A parallel SAT-based framework for closed frequent itemsets mining. CP 2018: 24th International Conference on Principles and Practice of Constraint Programming, Aug 2018, Lille, France. pp.570 - 587, ⟨10.1007/978-3-319-98334-9_37⟩. ⟨hal-01895369⟩
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