Extracting Frequent Gradual Patterns Based on SAT

Jerry Lonlac, Imen Dlala, Said Jabbour, Engelbert Nguifo, Badran Raddaoui, Lakhdar Sais

2023

Abstract

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.

Paper Citation

in Harvard Style

Lonlac J., Dlala I., Jabbour S., Nguifo E., Raddaoui B. and Sais L. (2023). Extracting Frequent Gradual Patterns Based on SAT. In Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA; ISBN 978-989-758-664-4, SciTePress, pages 136-143. DOI: 10.5220/0012126000003541

in Bibtex Style

@conference{data23,
author={Jerry Lonlac and Imen Dlala and Said Jabbour and Engelbert Nguifo and Badran Raddaoui and Lakhdar Sais},
title={Extracting Frequent Gradual Patterns Based on SAT},
booktitle={Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA},
year={2023},
pages={136-143},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012126000003541},
isbn={978-989-758-664-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Data Science, Technology and Applications - Volume 1: DATA
TI - Extracting Frequent Gradual Patterns Based on SAT
SN - 978-989-758-664-4
AU - Lonlac J.
AU - Dlala I.
AU - Jabbour S.
AU - Nguifo E.
AU - Raddaoui B.
AU - Sais L.
PY - 2023
SP - 136
EP - 143
DO - 10.5220/0012126000003541
PB - SciTePress