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On Maximal Frequent Itemsets Mining with Constraints

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Principles and Practice of Constraint Programming (CP 2018)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11008))

Abstract

Recently, a new declarative mining framework based on constraint programming (CP) and propositional satisfiability (SAT) has been designed to deal with several pattern mining tasks. The itemset mining problem has been modeled using constraints whose models correspond to the patterns to be mined. In this paper, we propose a new propositional satisfiability based approach for mining maximal frequent itemsets that extends the one proposed in [20]. We show that instead of adding constraints to the initial SAT based itemset mining encoding, the maximal itemsets can be obtained by performing clause learning during search. A major strength of our approach rises in the compactness of the proposed encoding and the efficiency of the SAT-based maximal itemsets enumeration derived using blocked clauses. Experimental results on several datasets, show the feasibility and the efficiency of our approach.

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Notes

  1. 1.

    A pseudo Boolean constraint over boolean variables is defined by \(\sum _{i} c_i.l_i \triangleright k\) where \(c_i\) are the coefficients, k an integer constant, \(l_i\) are literals and \(\triangleright \) is one of the operators \(\{=, <, \mathrel {\leqslant }, >, \mathrel {\geqslant }\}\).

  2. 2.

    http://fimi.ua.ac.be/data/.

  3. 3.

    http://dtai.cs.kuleuven.be/CP4IM/datasets/.

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Authors and Affiliations

  1. CRIL-CNRS, Université d’Artois, 62307, Lens Cedex, France

    Said Jabbour, Fatima Ezzahra Mana, Imen Ouled Dlala & Lakhdar Sais

  2. SAMOVAR, Télécom SudParis, CNRS, Univ. Paris-Saclay, Evry, France

    Badran Raddaoui

  3. INPT, Institut National des Postes et Telecommunications, Rabat, Morocco

    Fatima Ezzahra Mana

  4. LARODEC, University of Tunis, Tunis, Tunisia

    Imen Ouled Dlala

Authors
  1. Said Jabbour
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  2. Fatima Ezzahra Mana
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  3. Imen Ouled Dlala
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  4. Badran Raddaoui
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  5. Lakhdar Sais
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Correspondence to Lakhdar Sais .

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Editors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, PA, USA

    John Hooker

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Jabbour, S., Mana, F.E., Dlala, I.O., Raddaoui, B., Sais, L. (2018). On Maximal Frequent Itemsets Mining with Constraints. In: Hooker, J. (eds) Principles and Practice of Constraint Programming. CP 2018. Lecture Notes in Computer Science(), vol 11008. Springer, Cham. https://doi.org/10.1007/978-3-319-98334-9_36

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  • DOI: https://doi.org/10.1007/978-3-319-98334-9_36

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