A Constraint Programming Approach for Mining Sequential Patterns in a Sequence Database

Constraint-based pattern discovery is at the core of numerous data mining tasks. Patterns are extracted with respect to a given set of constraints (frequency, closedness, size, etc). In the context of sequential pattern mining, a large number of devoted techniques have been developed for solving particular classes of constraints. The aim of this paper is to investigate the use of Constraint Programming (CP) to model and mine sequential patterns in a sequence database. Our CP approach offers a natural way to simultaneously combine in a same framework a large set of constraints coming from various origins. Experiments show the feasibility and the interest of our approach

Discovering Knowledge using a Constraint-based Language

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 page

Crossing Boundaries: Tapestry Within the Context of the 21st Century

International audienceGraphical model processing is a central problem in artificial intelligence. The optimization of the combined cost of a network of local cost functions federates a variety of famous problems including CSP, SAT and Max-SAT but also optimization in stochastic variants such as Markov Random Fields and Bayesian networks. Exact solving methods for these problems typically include branch and bound and local inference-based bounds.In this paper we are interested in understanding when and how dynamic programming based optimization can be used to efficiently enforce soft local consistencies on Global Cost Functions, defined as parameterized families of cost functions of unbounded arity. Enforcing local consistencies in cost function networks is performed by applying so-called Equivalence Preserving Transformations (EPTs) to the cost functions. These EPTs may transform global cost functions and make them intractable to optimize.We identify as tractable projection-safe those global cost functions whose optimization is and remains tractable after applying the EPTs used for enforcing arc consistency. We also provide new classes of cost functions that are tractable projection-safe thanks to dynamic programming.We show that dynamic programming can either be directly used inside filtering algorithms, defining polynomially DAG-filterable cost functions, or emulated by arc consistency filtering on a Berge-acyclic network of bounded-arity cost functions, defining Berge-acyclic network-decomposable cost functions. We give examples of such cost functions and we provide a systematic way to define decompositions from existing decomposable global constraints.These two approaches to enforcing consistency in global cost functions are then embedded in a solver for extensive experiments that confirm the feasibility and efficiency of our proposal

A discontinuous Galerkin fast-sweeping Eikonal solver for fast and accurate traveltime computation in 3D tilted anisotropic media

International audienceWe tackle the challenging problem of efficient and accurate seismic traveltime computation in 3D anisotropic media, by applying the fast sweeping method to a discontinuous Galerkin-based Eikonal solver. Using this method leads to a stable and highly accurate scheme, which is faster than finite-difference schemes for given precision, and with a low computational cost compared to the standard Runge–Kutta discontinuous Galerkin formulation. The integral formulation of the discontinuous Galerkin method also makes it easy to handle seismic anisotropy and complex topographies. Several numerical tests on complex models, such as the 3D SEAM model, are given as illustration, highlighting the efficiency and the accuracy of this new approach. In the near future, these results will be used together with accurate solvers for seismic amplitude and take-off angle computation in order to revisit asymptotic inversion (traveltime/slope tomography) and imaging approaches (quantitative migration involving amplitudes and angles)

An accurate discontinuous Galerkin method for solving point-source Eikonal equation in 2-D heterogeneous anisotropic media

International audienceAccurate numerical computation of wave traveltimes in heterogeneous media is of major interest for a large range of applications in seismics, such as phase identification, data windowing, traveltime tomography and seismic imaging. A high level of precision is needed for traveltimes and their derivatives in applications which require quantities such as amplitude or take-off angle. Even more challenging is the anisotropic case, where the general Eikonal equation is a quartic in the derivatives of traveltimes. Despite their efficiency on Cartesian meshes, finite-difference solvers are inappropriate when dealing with unstructured meshes and irregular topographies. Moreover, reaching high orders of accuracy generally requires wide stencils and high additional computational load. To go beyond these limitations, we propose a discontinuous-finite-element-based strategy which has the following advantages: (1) the Hamiltonian formalism is general enough for handling the full anisotropic Eikonal equations; (2) the scheme is suitable for any desired high-order formulation or mixing of orders (p-adaptivity); (3) the solver is explicit whatever Hamiltonian is used (no need to find the roots of the quartic); (4) the use of unstructured meshes provides the flexibility for handling complex boundary geometries such as topographies (h-adaptivity) and radiation boundary conditions for mimicking an infinite medium. The point-source factorization principles are extended to this discontinuous Galerkin formulation. Extensive tests in smooth analytical media demonstrate the high accuracy of the method. Simulations in strongly heterogeneous media illustrate the solver robustness to realistic Earth-sciences-oriented applications

ASTRAL : un logiciel pour l'évaluation des conséquences d'un rejet accidentel de radionucléides dans l'environnement

ASTRAL est acronyme d'“ Assistance Technique en Radioprotection Post-accidentelle ”. Si un rejet important de radionucléides dans l'environnement se produisait, il faudrait rapidement évaluer la concentration des radionucléides dans les milieux et les produits alimentaires, en déduire l'exposition potentielle aux rayonnements des populations concernées, prévoir l'évolution de la situation et proposer différents scénarios de gestion des zones contaminées. A ces fins, il a été décidé il y trois ans environ de créer un logiciel utilisable par un ensemble relativement large d'agents gréant les centres de crise, réalisant des études prévisionnelles, ou s'occupant habituellement du contrôle de l'impact des rejets de routine. Le point de départ des estimations est le dépôt sur le sol des radionucléides. La phase de dispersion atmosphérique et les conséquences de l'exposition au nuage et aux radionucléides à vie courte ne sont pas traitées ici. Les calculs effectués concernent à la fois l'évolution dans le temps des concentrations des radionucléides dans les sols et les éléments de la chaîne alimentaire, ainsi que l'évaluation des doses efficaces dues à l'exposition externe et interne. Ces grandeurs sont comparées aux limites et niveaux d'intervention en vigueur. Différentes simulations de la gestion des zones contaminées peuvent être conduites par application de contre-mesures. Ainsi, le logiciel ASTRAL peut être utilisé comme un élément d'aide à la décision.