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Constraint Programming For Data Mining Material

Sequential Pattern mining to solve Sequential Pattern Mining Problem with/without time constraint

[PPIC][1] : Find all frequents sequences. Additional constraints are available as well. *Software + Code + Benchmarks

[PPICt][2] : Handle timed constraints (gap, span) over timed-datasets in sequential pattern mining. Additional constraints are available as well. *Software + Code + Benchmarks

Itemset Mining to solve 3 itemset mining problems: Frequent Itemset Mining, Frequent closed Itemset Mining and Discriminative (or correlated) Itemset Mining with the possibility to handle additional constraints.

[CoverSize][3] : Find all itemsets. Additional constraints are available as well. *Software + Code + Benchmarks

References

  1. An Efficient Algorithm for Mining Frequent Sequence with Constraint Programming, Aoga, John O. R., Guns Tias, and Schaus Pierre , Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part II, Cham, p.315–330, (2016)
  2. Mining Time-constrained Sequential Patterns with Constraint Programming, Aoga, John O. R., Guns Tias, and Schaus Pierre , Constraints, Volume 22, (2017)
  3. CoverSize: {A} Global Constraint for Frequency-Based Itemset Mining, Schaus, Pierre, Aoga John O. R., and Guns Tias , Principles and Practice of Constraint Programming: 23rd International Conference, {CP 2017}, Volume 10416, Melbourne, VIC, Australia, p.529–546, (2017)