Design of new algorithms for data mining with more flexiibity, modularity and efficiency by combining techniques of both worlds...Learn more
PPIC is a flexible and open source framework for Sequencial Pattern Mining. It uses Constraint programming approach to mine data based on PrefixSpan specialized method. It handles several user-defined constraints such as: Size constraint, Item constraint, Regular expression constraint.
PPDC is a variant of PPIC, using another support-counting approach for Sequencial Pattern Mining. It uses Constraint programming approach to mine data based on PrefixSpan specialized method. It handles several user-defined constraints such as: Size constraint, Item constraint, Regular expression constraint.
CoverSize is a flexible, efficient and open source framework for Frequent Itemset Mining (FIM) and two variants : Closed FIM and Discriminative FIM. It uses Constraint programming approach to mine data based. It handles several user-defined constraints such as: Size constraint, Item constraint.
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).
Mining Time-constrained Sequential Patterns with Constraint Programming, Aoga, John O. R., Guns Tias, and Schaus Pierre , Constraints, Volume 22, (2017).
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).