Interactive Pattern Mining Using Discriminant Sub-patterns as Dynamic Features

Autor: Arnold Hien, Samir Loudni, Noureddine Aribi, Abdelkader Ouali, Albrecht Zimmermann

Publikováno v: Advances in Knowledge Discovery and Data Mining ISBN: 9783031333736
Lecture Notes in Computer Science (LNAI)
PAKDD 2023: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining
PAKDD 2023: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Mar 2023, Osaka (Japon), Japan. pp.252-263, ⟨10.1007/978-3-031-33374-3_20⟩

International audience; Recent years have seen a shift from a pattern mining process that has users define constraints before-hand, and sift through the results afterwards, to an interactive one. This new framework depends on exploiting user feedback

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ae3c30140d0525b6c0f270388cf33d45
https://doi.org/10.1007/978-3-031-33374-3_20

Equitable optimized airspace sectorization based on constraint programming and OWA aggregation

Autor: Yahia Lebbah, Abdessamed Mogtit, Mohand Lagha, Noureddine Aribi

Publikováno v: Aircraft Engineering and Aerospace Technology. 92:1225-1243

Purpose Airspace sectorization is an important task, which has a significant impact in the everyday work of air control services. Especially in recent years, because of the constant increase in air traffic, existing airspace sectorization techniques

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::578a752dea6690c021dd63a21f1f8de1
https://doi.org/10.1108/aeat-04-2019-0080

A Relaxation-based Approach for Mining Diverse Closed Patterns

Autor: Noureddine Aribi, Abdelkader Ouali, Yahia Lebbah, Samir Loudni, Arnold Hien, Albrecht Zimmermann, Mohammed El Amine Laghzaoui

Publikováno v: Machine Learning and Knowledge Discovery in Databases-European Conference, {ECML} {PKDD} 2020
Machine Learning and Knowledge Discovery in Databases-European Conference, 2020, Sep 2020, Ghent (virtual), Belgium. pp.36--54, ⟨10.1007/978-3-030-67658-2_3⟩
HAL
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2020
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2020, Sep 2020, Gand, Belgium
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030676575
ECML/PKDD (1)

International audience; 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

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4250b803ee2a81076c61104d21ba5d1d
https://hal-imt-atlantique.archives-ouvertes.fr/hal-03244005/document

A Multiple Fault Localization Approach based on Multicriteria Analytical Hierarchy Process

Autor: Mehdi Maamar, Yahia Lebbah, Samir Loudni, Noureddine Aribi, Nadjib Lazaar

Publikováno v: 1st IEEE International Conference on Artificial Intelligence Testing
AiTest: Artificial Intelligence Testing
AiTest: Artificial Intelligence Testing, Apr 2019, San Francisco, United States. pp.1-8, ⟨10.1109/AITest.2019.00-16⟩
AITest

International audience; Fault localization problem is one of the most difficult processes in software debugging. Several spectrum-based ranking metrics have been proposed and none is shown to be empirically optimal. In this paper, we consider the fau

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7aa12772751599aeab19aca3a294b09a
https://hal-lirmm.ccsd.cnrs.fr/lirmm-02089746/document

Multiple Fault Localization Using Constraint Programming and Pattern Mining

Autor: Mehdi Maamar, Noureddine Aribi, Nadjib Lazaar, Samir Loudni, Yahia Lebbah

Publikováno v: ICTAI
IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI)
IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI), Nov 2017, Boston, United States. pp.860-867, ⟨10.1109/ICTAI.2017.00134⟩

International audience; Fault localization problem is one of the most difficult processes in software debugging. The current constraint-based approaches draw strength from declarative data mining and allow to consider the dependencies between stateme

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::32e6e30933c154b0ea7edc558cc0031c
https://doi.org/10.1109/ictai.2017.00134