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  1. Book ; Online: Boosting the Learning for Ranking Patterns

    Belmecheri, Nassim / Aribi, Noureddine / Lazaar, Nadjib / Lebbah, Yahia / Loudni, Samir

    2022  

    Abstract: Discovering relevant patterns for a particular user remains a challenging tasks in data mining. Several approaches have been proposed to learn user-specific pattern ranking functions. These approaches generalize well, but at the expense of the running ... ...

    Abstract Discovering relevant patterns for a particular user remains a challenging tasks in data mining. Several approaches have been proposed to learn user-specific pattern ranking functions. These approaches generalize well, but at the expense of the running time. On the other hand, several measures are often used to evaluate the interestingness of patterns, with the hope to reveal a ranking that is as close as possible to the user-specific ranking. In this paper, we formulate the problem of learning pattern ranking functions as a multicriteria decision making problem. Our approach aggregates different interestingness measures into a single weighted linear ranking function, using an interactive learning procedure that operates in either passive or active modes. A fast learning step is used for eliciting the weights of all the measures by mean of pairwise comparisons. This approach is based on Analytic Hierarchy Process (AHP), and a set of user-ranked patterns to build a preference matrix, which compares the importance of measures according to the user-specific interestingness. A sensitivity based heuristic is proposed for the active learning mode, in order to insure high quality results with few user ranking queries. Experiments conducted on well-known datasets show that our approach significantly reduces the running time and returns precise pattern ranking, while being robust to user-error compared with state-of-the-art approaches.
    Keywords Computer Science - Artificial Intelligence
    Subject code 006
    Publishing date 2022-03-05
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Book ; Online: Exploiting complex pattern features for interactive pattern mining

    Hien, Arnold / Loudni, Samir / Aribi, Noureddine / Ouali, Abdelkader / Zimmermann, Albrecht

    2022  

    Abstract: 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 to learn a quality function ...

    Abstract 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 to learn a quality function for patterns. Existing approaches have a weakness in that they use static pre-defined low-level features, and attempt to learn independent weights representing their importance to the user. As an alternative, we propose to work with more complex features that are derived directly from the pattern ranking imposed by the user. Learned weights are then aggregated onto lower-level features and help to drive the quality function in the right direction. We explore the effect of different parameter choices experimentally and find that using higher-complexity features leads to the selection of patterns that are better aligned with a hidden quality function while not adding significantly to the run times of the method. Getting good user feedback requires to quickly present diverse patterns, something that we achieve but pushing an existing diversity constraint into the sampling component of the interactive mining system LetSip. Resulting patterns allow in most cases to converge to a good solution more quickly. Combining the two improvements, finally, leads to an algorithm showing clear advantages over the existing state-of-the-art.
    Keywords Computer Science - Artificial Intelligence
    Subject code 006
    Publishing date 2022-04-08
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article: Exploiting tree decomposition for guiding neighborhoods exploration for VNS

    Fontaine, Mathieu / Boizumault, Patrice / Loudni, Samir

    RAIRO / Operations research Vol. 47, No. 2 , p. 91-123

    2013  Volume 47, Issue 2, Page(s) 91–123

    Author's details Mathieu Fontaine, Samir Loudni and Patrice Boizumault
    Keywords variable neighborhood search ; tree decomposition ; maximum cardinality search ; cost functions network ; constraint propagation
    Language English
    Size graph. Darst.
    Publisher EDP Sciences
    Publishing place Les Ulis
    Document type Article
    ZDB-ID 1481534-5 ; 1468388-x
    ISSN 1290-3868 ; 0399-0559
    ISSN (online) 1290-3868
    ISSN 0399-0559
    Database ECONomics Information System

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  4. Book ; Online: Discovering Knowledge using a Constraint-based Language

    Boizumault, Patrice / Crémilleux, Bruno / Khiari, Mehdi / Loudni, Samir / Métivier, Jean-Philippe

    2011  

    Abstract: Discovering pattern sets or global patterns is an attractive issue from the pattern mining community in order to provide useful information. By combining local patterns satisfying a joint meaning, this approach produces patterns of higher level and thus ... ...

    Abstract Discovering pattern sets or global patterns is an attractive issue from the pattern mining community in order to provide useful information. By combining local patterns satisfying a joint meaning, this approach produces patterns of higher level and thus more useful for the data analyst than the usual local patterns, while reducing the number of patterns. In parallel, recent works investigating relationships between data mining and constraint programming (CP) show that the CP paradigm is a nice framework to model and mine such patterns in a declarative and generic way. We present a constraint-based language which enables us to define queries addressing patterns sets and global patterns. The usefulness of such a declarative approach is highlighted by several examples coming from the clustering based on associations. This language has been implemented in the CP framework.

    Comment: 12 pages
    Keywords Computer Science - Machine Learning
    Publishing date 2011-07-18
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article: Filtrage de fonctions de coût globales décomposables

    Allouche, David / Bessiere, Christian / Boizumault, Patrice / De Givry, Simon / Gutierrez, Patricia / Loudni, Samir / Metivier, Jean-Philippe / Schiex, Thomas

    Actes des Huitièmes Journées Francophones de Programmation par Contraintes. 2012; Huitièmes Journées Francophones de Programmation par Contraintes (JFPC), Toulouse, FRA, 2012-05-22-2012-05-24, 15-24

    Abstract: Les auteurs de [18] ont montré que les problèmes de satisfaction de contraintes pondérées peuvent bénéficier de l’introduction des fonctions de coût globales, conduisant au nouveau paradigme de la programmation par fonctions de coûts. Dans cet article, ... ...

    Abstract Les auteurs de [18] ont montré que les problèmes de satisfaction de contraintes pondérées peuvent bénéficier de l’introduction des fonctions de coût globales, conduisant au nouveau paradigme de la programmation par fonctions de coûts. Dans cet article, nous explorons la possibilité de décomposer les fonctions de coût globales de sorte qu’appliquer une consistance locale souple sur la décomposition produit le même niveau de consistance que sur la fonction de coût initiale. Nous donnons des conditions pour lesquelles l’arc consistance directionelle et l’arc consistance virtuelle offrent de telles garanties. Nos expérimentations, menées sur des fonctions de coût décomposables, montrent que les décompositions peuvent être très utiles pour intégrer efficacement des fonctions de coût globales dans des solvers.
    Language fra
    Document type Article
    Database AGRIS - International Information System for the Agricultural Sciences and Technology

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    Inter-library loan at ZB MED

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  6. Article: Filtrage de fonctions de coût globales décomposables

    Allouche, David / Bessiere, Christian / Boizumault, Patrice / De Givry, Simon / Gutierrez, Patricia / Loudni, Samir / Metivier, Jean-Philippe / Schiex, Thomas

    Actes des Huitièmes Journées Francophones de Programmation par Contraintes. 2012; Huitièmes Journées Francophones de Programmation par Contraintes (JFPC), Toulouse, FRA, 2012-05-22-2012-05-24, 15-24

    Abstract: Les auteurs de [18] ont montré que les problèmes de satisfaction de contraintes pondérées peuvent bénéficier de l’introduction des fonctions de coût globales, conduisant au nouveau paradigme de la programmation par fonctions de coûts. Dans cet article, ... ...

    Abstract Les auteurs de [18] ont montré que les problèmes de satisfaction de contraintes pondérées peuvent bénéficier de l’introduction des fonctions de coût globales, conduisant au nouveau paradigme de la programmation par fonctions de coûts. Dans cet article, nous explorons la possibilité de décomposer les fonctions de coût globales de sorte qu’appliquer une consistance locale souple sur la décomposition produit le même niveau de consistance que sur la fonction de coût initiale. Nous donnons des conditions pour lesquelles l’arc consistance directionelle et l’arc consistance virtuelle offrent de telles garanties. Nos expérimentations, menées sur des fonctions de coût décomposables, montrent que les décompositions peuvent être très utiles pour intégrer efficacement des fonctions de coût globales dans des solvers.
    Language fra
    Document type Article
    Database AGRIS - International Information System for the Agricultural Sciences and Technology

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    Inter-library loan at ZB MED

    Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

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