Littérature scientifique sur le sujet « Graphes relationnels »
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Articles de revues sur le sujet "Graphes relationnels"
Morel, Didier. « Une intelligence relationnelle ». Le sociographe 33, no 3 (2010) : 25. http://dx.doi.org/10.3917/graph.033.0025.
Texte intégralLeavy, Normand. « Aspects techniques d'un projet de recherche sur l'influence ». Notes de recherche 18, no 2 (12 avril 2005) : 271–86. http://dx.doi.org/10.7202/055750ar.
Texte intégralFacchinetti-Mannone, Valérie. « Nodality of french suburban high speed train stations ». Les Cahiers Scientifiques du Transport - Scientific Papers in Transportation 48 | 2005 (30 novembre 2005). http://dx.doi.org/10.46298/cst.12036.
Texte intégralFaye, David C., Gilles Nachouki et Patrick Valduriez. « SenPeer : un système pair-à-pair de médiation de données ». Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées Volume 4, 2006 (20 octobre 2006). http://dx.doi.org/10.46298/arima.1847.
Texte intégralThèses sur le sujet "Graphes relationnels"
Jacob, Yann. « Classification dans les graphes hétérogènes et multi-relationnels avec contenu : Application aux réseaux sociaux ». Paris 6, 2013. http://www.theses.fr/2013PA066494.
Texte intégralThe emergence of the Web 2. 0 has seen the apparition of a large quantity of data that can easily be represented as complex graphs. There is many tasks of information analysis, prediction and retrieval on these data, while the state-of-the-art models are not adapted. In this thesis, we consider the task of node classification/labeling in complex partially labeled content networks. The applications for this task are for instance video/photo annotation in the Web 2. 0 websites, web spam detection or user labeling in social networks. The originality of our work is that we focus on two types of complex networks rarely considered in existing works: \textbf{multi-relationnal graphs} composed of multiple relation types and \textbf{heterogeneous networks} composed of multiple node types then of multiple joint labeling problems. First, we proposed two new algorithms for multi-relationnal graph labeling. These algorithms learn to weight the different relation types in the label propagation process according to their usefullness for the labeling task. They learn to combine the different relation types in an optimal manner for classification, while using the node content information. Then, we proposed an algorithm for heterogeneous graph labeling. Here, a specific problem is that each type of node has it own label set: for instance visual tags for a photo and groups for an user, then we must solve these different classification problems simultaneously using the graph structure. Our algorithm is based on the usage of a latent representation common to all node types allowing to process the different node types in an uniformized manner. Our experimental results show that this model is able to take in account the correlations between labels of different node types
Wendling, Laurent. « Segmentation floue appliquée à la recherche d'objets dans les images numériques. Graphes relationnels et reconnaissance des formes. Application à la détection d'objets dans les images sur la base d'exemples ». Toulouse 3, 1997. http://www.theses.fr/1997TOU30041.
Texte intégralGONZáLEZ, GóMEZ Mauricio. « Jeux stochastiques sur des graphes avec des applications à l’optimisation des smart-grids ». Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLN064.
Texte intégralWithin the research community, there is a great interest in exploring many applications of energy grids since these become more and more important in our modern world. To properly design and implement these networks, advanced and complex mathematical tools are necessary. Two key features for their design are correctness and optimality. While these last two properties are in the core of formal methods, their effective application to energy networks remains largely unexploited. This constitutes one strong motivation for the work developed in this thesis. A special emphasis is made on the generic problem of scheduling power consumption. This is a scenario in which the consumers have a certain energy demand and want to have this demand fulfilled before a set deadline (e.g., an Electric Vehicle (EV) has to be recharged within a given time window set by the EV owner). Therefore, each consumer has to choose at each time the consumption power (by a computerized system) so that the final accumulated energy reaches a desired level. The way in which the power levels are chosen is according to a ``strategy’’ mapping at any time the relevant information of a consumer (e.g., the current accumulated energy for EV-charging) to a suitable power consumption level. The design of such strategies may be either centralized (in which there is a single decision-maker controlling all strategies of consumers), or decentralized (in which there are several decision-makers, each of them representing a consumer). We analyze both scenarios by exploiting ideas originating from formal methods, game theory and optimization. More specifically, the power consumption scheduling problem can be modelled using Markov decision processes and stochastic games. For instance, probabilities provide a way to model the environment of the electrical system, namely: the noncontrollable part of the total consumption (e.g., the non-EV consumption). The controllable consumption can be adapted to the constraints of the distribution network (e.g., to the maximum shutdown temperature of the electrical transformer), and to their objectives (e.g., all EVs are recharged). At first glance, this can be seen as a stochastic system with multi-constraints objectives. Therefore, the contributions of this thesis also concern the area of multi-criteria objective models, which allows one to pursue several objectives at a time such as having strategy designs functionally correct and robust against changes of the environment
Munch, Mélanie. « Améliorer le raisonnement dans l'incertain en combinant les modèles relationnels probabilistes et la connaissance experte ». Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASB011.
Texte intégralThis thesis focuses on integrating expert knowledge to enhance reasoning under uncertainty. Our goal is to guide the probabilistic relations’ learning with expert knowledge for domains described by ontologies.To do so we propose to couple knowledge bases (KBs) and an oriented-object extension of Bayesian networks, the probabilistic relational models (PRMs). Our aim is to complement the statistical learning with expert knowledge in order to learn a model as close as possible to the reality and analyze it quantitatively (with probabilistic relations) and qualitatively (with causal discovery). We developped three algorithms throught three distinct approaches, whose main differences lie in their automatisation and the integration (or not) of human expert supervision.The originality of our work is the combination of two broadly opposed philosophies: while the Bayesian approach favors the statistical analysis of the given data in order to reason with it, the ontological approach is based on the modelization of expert knowledge to represent a domain. Combining the strenght of the two allows to improve both the reasoning under uncertainty and the expert knowledge
Haugeard, Jean-Emmanuel. « Extraction et reconnaissance de primitives dans les façades de Paris à l'aide d'appariement de graphes ». Thesis, Cergy-Pontoise, 2010. http://www.theses.fr/2010CERG0497.
Texte intégralThis last decade, modeling of 3D city became one of the challenges of multimedia search and an important focus in object recognition. In this thesis we are interested to locate various primitive, especially the windows, in the facades of Paris. At first, we present an analysis of the facades and windows properties. Then we propose an algorithm able to extract automatically window candidates. In a second part, we discuss about extraction and recognition primitives using graph matching of contours. Indeed an image of contours is readable by the human eye, which uses perceptual grouping and makes distinction between entities present in the scene. It is this mechanism that we have tried to replicate. The image is represented as a graph of adjacency of segments of contours, valued by information orientation and proximity to edge segments. For the inexact matching of graphs, we propose several variants of a new similarity based on sets of paths, able to group several contours and robust to scale changes. The similarity between paths takes into account the similarity of sets of segments of contours and the similarity of the regions defined by these paths. The selection of images from a database containing a particular object is done using a KNN or SVM classifier
Ounis, Iadh. « Un modèle d'indexation relationnel pour les graphes conceptuels fondé sur une interprétation logique ». Phd thesis, Université Joseph Fourier (Grenoble), 1998. http://tel.archives-ouvertes.fr/tel-00004902.
Texte intégralRoux, Bernard. « Une approche relationnelle des automates et de l'ordonnancement ». Lyon 1, 2000. http://www.theses.fr/2000LYO10255.
Texte intégralPoulain, Rémy. « Analyse et modélisation de la diversité des structures relationnelles à l'aide de graphes multipartis ». Electronic Thesis or Diss., Sorbonne université, 2020. http://www.theses.fr/2020SORUS453.
Texte intégralThere is no longer any need to prove that digital technology, the Internet and the web have led to a revolution, particularly in the way people get information. Like any revolution, it is followed by a series of issues : equal treatment of users and suppliers, ecologically sustainable consumption, freedom of expression and censorship, etc. Research needs to provide a clear vision of these stakes. Among these issues, we can talk about two phenomena : the echo chamber phenomenon and the filter bubble phenomenon. These two phenomena are linked to the lack of diversity of information visible on the Internet, and one may wonder about the impact of recommendation algorithms. Even if this is our primary motivation, we are moving away from this subject to propose a general scientific framework to analyze diversity. We find that the graph formalism is useful enough to be able to represent relational data. More precisely, we will analyze relational data with entities of different natures. This is why we chose the n-part graph formalism because this is a good way to represent a great diversity of data. Even if the first data we studied is related to recommendation algorithms (music consumption or purchase of articles on a platform) we will see over the course of the manuscript how this formalism can be adapted to other types of data (politicized users on Twitter, guests of television shows, establishment of NGOs in different States ...). There are several objectives in this study : — Mathematically define diversity indicators on the n-part graphs. — Algorithmically define how to calculate them. — Program these algorithms to make them a usable computer object. — Use these programs on quite varied data. — See the different meanings that our indicators can have. We will begin by describing the mathematical formalism necessary for our study. Then we will apply our mathematical object to basic examples to see all the possibilities that our object offers us. This will show us the importance of normalizing our indicators, and will motivate us to study random normalization. Then we will see another series of examples which will allow us to go further on our indicators, going beyond the static and tripartite side to approach graphs with more layers and depending on time. To be able to have a better vision of what the real data brings us, we will study our indicators on completely randomly generated graphs
Haugeard, Jean-Emmanuel. « Extraction et reconnaissance de primitives dans les façades de Paris à l'aide de similarités de graphes ». Phd thesis, Université de Cergy Pontoise, 2010. http://tel.archives-ouvertes.fr/tel-00593985.
Texte intégralRuoppolo, Domenico. « Relational graph models and Morris's observability : resource-sensitive semantic investigations on the untyped λ-calculus ». Thesis, Sorbonne Paris Cité, 2016. http://www.theses.fr/2016USPCD069/document.
Texte intégralThis thesis is a contribution to the study of Church’s untyped λ-calculus, a term rewritingsystem having the β-reduction (the formal counterpart of the idea of execution of programs) asmain rule. The focus is on denotational semantics, namely the investigation of mathematical models of the λ-calculus giving the same denotation to β-convertible λ-terms. We investigate relational semantics, a resource-sensitive semantics interpreting λ-terms as relations,with their inputs grouped together in multisets. We define a large class of relational models,called relational graph models (rgm’s), and we study them in a type/proof-theoretical way, using some non-idempotent intersection type systems. Firstly, we find the minimal and maximal λ-theories (equational theories extending -conversion) represented by the class.Then we use rgm’s to solve the full abstraction problem for Morris’s observational λ-theory,the contextual equivalence of programs that one gets by taking the β-normal forms asobservable outputs. We solve the problem in different ways. Through a type-theoretical characterization of β-normalizability, we find infinitely many fully abstract rgm’s, that wecall uniformly bottomless.We then give an exhaustive answer to the problem, by showing thatan rgm is fully abstract for Morris’s observability if and only if it is extensional (a model of ŋ-conversion) and λ-König. Intuitively an rgm is λ-König when every infinite computable tree has an infinite branch witnessed by some type of the model, where the witnessing is a property of non-well-foundedness on the type