%0 Conference Proceedings %T A Relaxation-based Approach for Mining Diverse Closed Patterns %+ Equipe CODAG - Laboratoire GREYC - UMR6072 %+ Département Automatique, Productique et Informatique (IMT Atlantique - DAPI) %+ Théorie, Algorithmes et Systèmes en Contraintes (LS2N - équipe TASC ) %+ Laboratoire d'Informatique et Technologies de l'Information d'Oran (LITIO) %A Hien, Arnold %A Loudni, Samir %A Aribi, Noureddine %A Lebbah, Yahia %A Laghzaoui, Mohammed El Amine %A Ouali, Abdelkader %A Zimmermann, Albrecht %< avec comité de lecture %B Machine Learning and Knowledge Discovery in Databases - European Conference, {ECML} {PKDD} 2020 %C Ghent (virtual), Belgium %Y Frank Hutter %Y Kristian Kersting %Y Jefrey Lijffijt %Y Isabel Valera %I Springer %3 Lecture Notes in Computer Science %N 12457 %P 36--54 %8 2020-09-14 %D 2020 %R 10.1007/978-3-030-67658-2_3 %K Data mining DM %K Constraint programming %K Diversity Constraints %Z Computer Science [cs]/Artificial Intelligence [cs.AI]Conference papers %X In recent years, pattern mining has moved from a slow-moving repeated three-step process to a much more agile iterative/user-centric mining model. A vital ingredient of this framework is the ability to quickly present a set of diverse patterns to the user. In this paper, we use constraint programming (wellsuited to user-centric mining due to its rich constraint language) to efficiently mine a diverse set of closed patterns. Diversity is controlled through a threshold on the Jaccard similarity of pattern occurrences. We show that the Jaccard measure has no monotonicity property, which prevents usual pruning techniques and makes classical pattern mining unworkable. This is why we propose antimonotonic lower and upper bound relaxations, which allow effective pruning, with an efficient branching rule, boosting the whole search process. We show experimentally that our approach significantly reduces the number of patterns and is very efficient in terms of running times, particularly on dense data sets. %G English %2 https://imt-atlantique.hal.science/hal-03244005/document %2 https://imt-atlantique.hal.science/hal-03244005/file/sub_788.pdf %L hal-03244005 %U https://imt-atlantique.hal.science/hal-03244005 %~ UNIV-NANTES %~ INSTITUT-TELECOM %~ CNRS %~ EC-NANTES %~ UNAM %~ GREYC %~ GREYC-CODAG %~ COMUE-NORMANDIE %~ LS2N %~ LS2N-TASC %~ LS2N-TASC-IMTA %~ IMTA_DAPI %~ LS2N-IMTA %~ ENSICAEN %~ UNICAEN %~ IMT-ATLANTIQUE %~ INSTITUTS-TELECOM %~ NANTES-UNIVERSITE %~ UNIV-NANTES-AV2022 %~ NU-CENTRALE