Search results for "ML"

Une approche structurelle pour la reconnaissance de notices bibliographiques

1995

National audience; Cet article présente un système de reconnaissance de la structure logique de notices bibliographiques en vue de la conversion rétrospective de catalogues de bibliothèques. Le système est guidé par un modèle de structures de la classe des notices, construit sur la base de spécifications détaillées par la bibliothèque. Le modèle fait intervenir aussi bien des connaissances sur la macro-structure des notices que sur la micro-structure de leur contenu. La reconnaissance de la structure d'une notice consiste à retrouver, à partir d'un flux OCR (Optical Character Recognition), sa structure logique spécifique, conformément aux descriptions du modèle. Le résultat est un flux stru…

Toward Approximate GML Retrieval Based on Structural and Semantic Characteristics

2010

International audience; GML is emerging as the new standard for representing geographic information in GISs on the Web, allowing the encoding of structurally and semantically rich geographic data in self describing XML-based geographic entities. In this study, we address the problem of approximate querying and ranked results for GML data and provide a method for GML query evaluation. Our method consists of two main contributions. First, we propose a tree model for representing GML queries and data collections. Then, we introduce a GML retrieval method based on the concept of tree edit distance as an efficient means for comparing semi-structured data. Our approach allows the evaluation of bo…

Semantic-based Merging of RSS Items

2009

Merging XML documents can be of key importance in several applications. For instance, merging the RSS news from same or different sources and providers can be beneficial for end-users in various scenarios. In this paper, we address this issue and explore the relatedness measure between RSS elements. We show here how to define and compute exclusive relations between any two elements and provide several predefined merging operators that can be extended and adapted to human needs. We also provide a set of experiments conducted to validate our approach. © Springer Science+Business Media, LLC 2009.

Enforcing role based access control model with multimedia signatures.

2009

International audience; Recently ubiquitous technology has invaded almost every aspect of the modern life. Several application domains, have integrated ubiquitous technology to make the management of resources a dynamic task. However, the need for adequate and enforced authentication and access control models to provide safe access to sensitive information remains a critical matter to address in such environments. Many security models were proposed in the literature thus few were able to provide adaptive access decisions based on the environmental changes. In this paper, we propose an approach based on our previous work [B.A. Bouna, R. Chbeir, S. Marrara, A multimedia access control languag…

Semantic aware RSS query algebra

2010

International audience; Existing XML query algebras are not fully appropriate to retrieve RSS news items mainly due to three reasons: 1) RSS is text rich and its content is dependent on the wording and verbification of the author, thus semantic aware operators are needed; 2) news items are dynamic and consequently time oriented retrieval is needed; 3) a news item may evolve through time, or overlap with other news items and hence identifying relationships between items is also needed. In this paper, we aim to solve these issues by providing a dedicated RSS algebra based on semantic-aware operators that consider RSS characteristics. The provided operators are application domain specific and …

RDF2SPIN: Mapping Semantic Graphs to SPIN Model Checker

2011

International audience; The most frequently used language to represent the semantic graphs is the RDF (W3C standard for meta-modeling). The construction of semantic graphs is a source of numerous errors of interpretation. The processing of large semantic graphs is a limit to the use of semantics in current information systems. The work presented in this paper is part of a new research at the border between two areas: the semantic web and the model checking. For this, we developed a tool, RDF2SPIN, which converts RDF graphs into SPIN language. This conversion aims checking the semantic graphs with the model checker SPIN in order to verify the consistency of the data. To illustrate our propos…

Characterizations of convex approximate subdifferential calculus in Banach spaces

2016

International audience; We establish subdifferential calculus rules for the sum of convex functions defined on normed spaces. This is achieved by means of a condition relying on the continuity behaviour of the inf-convolution of their corresponding conjugates, with respect to any given topology intermediate between the norm and the weak* topologies on the dual space. Such a condition turns out to also be necessary in Banach spaces. These results extend both the classical formulas by Hiriart-Urruty and Phelps and by Thibault.

Construction de Modèles Prédictifs pour l'Analyse des Relations Oiseaux-Paysage

2013

National audience; Cet article présente une comparaison de trois méthodes (Modèles Linéaires Généralisés, Réseaux de Neurones, Machines Vecteurs Supports) et de différentes combinaisons de prétraitements de données (filtrage, arrondi, analyse factorielle, sélection de paramètres). L'objectif de cette comparaison est de définir quel est le processus qui permet de construire le meilleur modèle prédictif, dans le cadre de la prédiction d'abondances d'espèces d'oiseaux à partir de variables décrivant le paysage. Nous comparerons les modèles grâce à l'erreur moyenne absolue et à l'information mutuelle. Cette comparaison a montré qu'aucune technique étudiée ne permet de construire des modèles pré…

Numerical models contribute to expand the sweet taste chemical space

2021

A Neural Network Meta-Model and its Application for Manufacturing

2015

International audience; Manufacturing generates a vast amount of data both from operations and simulation. Extracting appropriate information from this data can provide insights to increase a manufacturer's competitive advantage through improved sustainability, productivity, and flexibility of their operations. Manufacturers, as well as other industries, have successfully applied a promising statistical learning technique, called neural networks (NNs), to extract meaningful information from large data sets, so called big data. However, the application of NN to manufacturing problems remains limited because it involves the specialized skills of a data scientist. This paper introduces an appr…