2 citations · 4 across the 3 of their papers we have counts for
4 papers
Extracting Seasonal Gradual Patterns from Temporal Sequence Data Using Periodic Patterns Mining
Jerry Lonlac, Arnaud Doniec, Marin Lujak +1
Mining frequent episodes aims at recovering sequential patterns from temporal data sequences, which can then be used to predict the occurrence of related events in advance. On the…
Discovering Frequent Gradual Itemsets with Imprecise Data
Michaël Chirmeni Boujike, Jerry Lonlac, Norbert Tsopze +1
The gradual patterns that model the complex co-variations of attributes of the form "The more/less X, The more/less Y" play a crucial role in many real world applications where the…
Extracting Frequent Gradual Patterns Using Constraints Modeling
Jerry Lonlac, Saïdd Jabbour, Engelbert Mephu Nguifo +2
In this paper, we propose a constraint-based modeling approach for the problem of discovering frequent gradual patterns in a numerical dataset. This SAT-based declarative approach…
Towards Learned Clauses Database Reduction Strategies Based on Dominance Relationship
Jerry Lonlac, Engelbert Mephu Nguifo
Clause Learning is one of the most important components of a conflict driven clause learning (CDCL) SAT solver that is effective on industrial instances. Since the number of learne…