Extracting frequent gradual patterns based on SAT
Résumé
This paper proposes a constraint-based modeling approach for mining frequent gradual patterns from numerical data. Our declarative approach provides a principle way to take advantage of recent advancements in satisfiability testing and several features of modern SAT solvers to enumerating gradual patterns. Interestingly, our approach can easily be extended with extra requirements, such as temporal constraints used to extract more specific patterns in a broad range of gradual patterns mining applications. An empirical evaluation on two real-word datasets shows the efficiency of our approach.
