Tesi sul tema "Analyse des graphes dynamiques"
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Albano, Alice. "Dynamique des graphes de terrain : analyse en temps intrinsèque". Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066260/document.
Testo completoWe are surrounded by a multitude of interaction networks from different contexts. These networks can be modeled as graphs, called complex networks. They have a community structure, i.e. groups of nodes closely related to each other and less connected with the rest of the graph. An other phenomenon studied in complex networks in many contexts is diffusion. The spread of a disease is an example of diffusion. These phenomena are dynamic and depend on an important parameter, which is often little studied: the time scale in which they are observed. According to the chosen scale, the graph dynamics can vary significantly. In this thesis, we propose to study dynamic processes using a suitable time scale. We consider a notion of relative time which we call intrinsic time, opposed to "traditional" time, which we call extrinsic time. We first study diffusion phenomena using intrinsic time, and we compare our results with an extrinsic time scale. This allows us to highlight the fact that the same phenomenon observed at two different time scales can have a very different behavior. We then analyze the relevance of the use of intrinsic time scale for detecting dynamic communities. Comparing communities obtained according extrinsic and intrinsic scales shows that the intrinsic time scale allows a more significant detection than extrinsic time scale
Albano, Alice. "Dynamique des graphes de terrain : analyse en temps intrinsèque". Electronic Thesis or Diss., Paris 6, 2014. http://www.theses.fr/2014PA066260.
Testo completoWe are surrounded by a multitude of interaction networks from different contexts. These networks can be modeled as graphs, called complex networks. They have a community structure, i.e. groups of nodes closely related to each other and less connected with the rest of the graph. An other phenomenon studied in complex networks in many contexts is diffusion. The spread of a disease is an example of diffusion. These phenomena are dynamic and depend on an important parameter, which is often little studied: the time scale in which they are observed. According to the chosen scale, the graph dynamics can vary significantly. In this thesis, we propose to study dynamic processes using a suitable time scale. We consider a notion of relative time which we call intrinsic time, opposed to "traditional" time, which we call extrinsic time. We first study diffusion phenomena using intrinsic time, and we compare our results with an extrinsic time scale. This allows us to highlight the fact that the same phenomenon observed at two different time scales can have a very different behavior. We then analyze the relevance of the use of intrinsic time scale for detecting dynamic communities. Comparing communities obtained according extrinsic and intrinsic scales shows that the intrinsic time scale allows a more significant detection than extrinsic time scale
Mostefaoui, Mustapha. "Analyse des propriétés temporelles des graphes d'événements valués continus". Nantes, 2001. http://www.theses.fr/2001NANT2100.
Testo completoVENET, ARNAUD. "Analyse statique des systemes dynamiques de graphes dans les langages non types". Palaiseau, Ecole polytechnique, 1998. http://www.theses.fr/1998EPXX0073.
Testo completoBridonneau, Vincent. "Generation and Analysis of Dynamic Graphs". Electronic Thesis or Diss., Normandie, 2024. http://www.theses.fr/2024NORMLH23.
Testo completoIn this thesis, we investigate iterative processes producing a flow of graphs. These processes findapplications both in complex networks and time-varying graphs. Starting from an initial configurationcalled a seed, these processes produce a continuous flow of graphs. A key question arises when theseprocesses impose no constraints on the size of the generated graphs: under what conditions can we ensurethat the graphs do not become empty? And how can we account for the changes between successive stepsof the process? To address the first question, we introduced the concept of sustainability, which verifieswhether an iterative process is likely to produce graphs with periodic behaviors. We defined and studied agraph generator that highlights the many challenges encountered when exploring this notion. Regardingthe second question, we designed a metric to quantify the changes occurring between two consecutive stepsof the process. This metric was tested on various generators as well as on real-world data, demonstratingits ability to capture the dynamics of a network, whether artificial or real. The study of these two conceptshas opened the door to many new questions and strengthened the connections between complex networkanalysis and temporal graph theory
Gautero, François. "CW-complexes dynamiques". Nice, 1998. http://www.theses.fr/1998NICE5137.
Testo completoCasteigts, Arnaud. "Contribution à l'algorithmique distribuée dans les réseaux mobiles ad hocCalculs locaux et réétiquetages de graphes dynamiques". Bordeaux 1, 2007. http://www.theses.fr/2007BOR13430.
Testo completoGilbert, Frédéric. "Méthodes et modèles pour la visualisation de grandes masses de données multidimensionnelles nominatives dynamiques". Thesis, Bordeaux 1, 2012. http://www.theses.fr/2012BOR14498/document.
Testo completoSince ten years, informations visualization domain knows a real interest.Recently, with the growing of communications, the research on social networks analysis becomes strongly active. In this thesis, we present results on dynamic social networks analysis. That means that we take into account the temporal aspect of data. We were particularly interested in communities extraction within networks and their evolutions through time. [...]
Delanoue, Nicolas. "Algorithmes numériques pour l'analyse topologique : Analyse par intervalles et théorie des graphes". Phd thesis, Université d'Angers, 2006. http://tel.archives-ouvertes.fr/tel-00340999.
Testo completoDe nombreux problèmes, comme l'étude de l'espace des configurations d'un robot, se ramènent à une étude qualitative d'ensembles. Ici, la ``taille'' de l'ensemble importe peu, ce qui compte, c'est sa ``topologie''. Les méthodes proposées calculent des invariants topologiques d'ensembles. Les ensembles considérés sont décrits à l'aide d'inégalités $\mathcal{C}^{\infty}$. L'idée maîtresse est de décomposer un ensemble donné en parties contractiles et d'utiliser l'homologie de \v Cech.
La seconde partie de la thèse concerne l'étude de point
asymptotiquement stables des systèmes dynamiques (linéaires ou non). Plus largement, on propose une méthode pour approcher le bassin d'attraction d'un point asymptotiquement stable. Dans un premier temps, on utilise la théorie de Lyapunov et le calcul par intervalle
pour trouver effectivement un voisinage inclus dans le bassin d'attraction d'un point prouvé asymptotiquement stable. Puis, on combine, une fois de plus, la théorie des graphes et les méthodes d'intégration d'équations différentielles ordinaires pour améliorer ce voisinage et ainsi construire un ensemble inclus dans le bassin
d'attraction de ce point.
Martinet, Lucie. "Réseaux dynamiques de terrain : caractérisation et propriétés de diffusion en milieu hospitalier". Thesis, Lyon, École normale supérieure, 2015. http://www.theses.fr/2015ENSL1010/document.
Testo completoIn this thesis, we focus on tools whose aim is to extract structural and temporal properties of dynamic networks as well as diffusion characteristics which can occur on these networks. We work on specific data, from the European MOSAR project, including the network of individuals proximity from time to time during 6 months at the Brek-sur-Mer Hospital. The studied network is notable because of its three dimensions constitution : the structural one induced by the distribution of individuals into distinct services, the functional dimension due to the partition of individual into groups of socio-professional categories and the temporal dimension.For each dimension, we used tools well known from the areas of statistical physics as well as graphs theory in order to extract information which enable to describe the network properties. These methods underline the specific structure of the contacts distribution which follows the individuals distribution into services. We also highlight strong links within specific socio-professional categories. Regarding the temporal part, we extract circadian and weekly patterns and quantify the similarities of these activities. We also notice distinct behaviour within patients and staff evolution. In addition, we present tools to compare the network activity within two given periods. To finish, we use simulations techniques to extract diffusion properties of the network to find some clues in order to establish a prevention policy
Vimont, Guillaume. "Approximation dynamique de clusters dans un graphe social : méthodes et applications". Thesis, Paris 2, 2019. http://www.theses.fr/2019PA020007.
Testo completoWe study how to detect clusters in a graph defined by a stream of edges, without storing the entire graph. We show how to detect large clusters in the order of √n in graphs that have m = O(n log(n)) edges, while storing √n.log(n) edges. Social graphs satisfy this condition m. We extend our approach to dynamic graphs defined by the most recent stream of edges and multiple streams. We propose simple and robust methods based on the approximation to detect these clusters.We define the content correlation of two streams ρ(t) is the Jaccard similarity of their clusters in the windows before time t. We propose a simple and efficient method to approach this online correlation and show that for dynamic random graphs that follow a power law, we can guarantee a good approximation.As an applications we follow Twitter streams and compute their content correlations online. We then propose a search by correlation where answers to sets of keywords are entirely based on the small correlations of the streams. Answers are ordered by the correlations, and explanations can be traced with the stored clusters
Démare, Thibaut. "Une approche systémique à base d'agents et de graphes dynamiques pour modéliser l'interface logistique port-métropole". Thesis, Le Havre, 2016. http://www.theses.fr/2016LEHA0021/document.
Testo completoA logistic system is an essential component of a spatial system. Actors are organised around infrastructures in order to move different kinds of flow (of goods, of information, or financial) over a territory. The logistic organisation comes from an auto-organised and distributed process from the actors. This works aims to understand, at different scales, how autonomous and heterogeneous actors (according to their goals and methods to take decisions) are collectively organised around infrastructures to manage different kinds of flow, and despite numerous constraints (temporal, spatial,...). We propose an agent-based model which allows to simulate the processes to create and organise logistic flow over a territory. The model describes an interface between international and urban flow in order to understand how the port and urban dynamics work together. The model integrates a structural and organisational dynamics thanks to dynamic graphs in order to represent the evolution of this kind of system. Thus, the agents can adapt themselves to system's perturbations as in the reality
Jahel, Camille. "Analyse des dynamiques des agroécosystèmes par modélisation spatialisée et utilisation d’images satellitaires, Cas d’étude de l’ouest du Burkina Faso". Electronic Thesis or Diss., Paris, AgroParisTech, 2016. http://www.theses.fr/2016AGPT0059.
Testo completoRural areas of West Africa have seen notable transformations these last two decades, mainly due to high population growth, development policies in favor of export crops and introduction of new cropping practices. The results of these developments are a pressure on forestry resources, an evolution of farming systems, a depletion of soils and a saturation of cultivated areas. The number of conflicts for resources access increases, reviving buried ethnical tensions, and the question of food security is raised. In that context, early warning systems have been developed in order to foresee and curb food insecurity by the mean of hazard analyses.The present work deals with agrarian changes and their mechanisms, in the context of early warning systems development. New methodological approaches are explored, based on modeling and remote sensing in order to create a retrospective and prospective analysis of agrarian dynamics of the Tuy province, located in West Burkina Faso.We first focus on the issue of cross-scaling in agro-ecosystems dynamics models, by building a multi-scalar model of past developments. The model uses interaction graphs to simulate processes occurring from the plot scale to the regional scale (crop production, crop rotation and crop area expansion). We show that modelling across scales is achievable without resorting to methods of aggregation or disaggregation, usually applied for this type of study.The model is then used to analyze two aspects of agrarian dynamics of Tuy province. The first one deals with clearances dynamics in the context of Malthus vs Boserup debate, concerning the impacts of demographic growth on natural resources. Prospective scenarios are simulated and their consequences on natural vegetation surfaces are assessed: these scenarios simulate emigrations of a part of the population towards other areas, the implementation of protected areas, a demographic regulation and an ecological intensification of farming systems.The second aspect concerns decisional processes of farmers in order to constitute their crops rotations. The study consists in understanding the important variations of cultivated species, observed during the studied period, by analyzing the simulated weight evolution of different determining factors involved in the decisional processes.Finally, we show that anthropic processes footprints are explicitly detectable in remote sensing images, by using multi-scalar simulations of the model developed. Then, we create an assimilation of satellite data in the model in order to re-calibrate it and reinforce its abilities to reproduce past dynamics. This last part opens important perspectives concerning the joint use of remote sensing data and agro-ecosystems dynamics
Seifi, Massoud. "Coeurs stables de communautés dans les graphes de terrain". Paris 6, 2012. http://www.theses.fr/2012PA066058.
Testo completoIn many contexts, sets of related entities can be modeled by graphs, in which entities are represented by nodes and relationships between these entities by edges. These graphs, which we call "complex networks", may be encountered in the real world in various fields such as social science, computer science, biology, transportation, linguistics, etc. Most complex networks are composed of dense subgraphs weakly interconnected called "communities" and many algorithms have been proposed to identify the community structure of complex networks automatically. During this thesis, we focused on the problems of community detection algorithms, especially their non-determinism and the instability that results. We presented a methodology that takes advantage of this non-determinism to improve the results obtained with current community detection techniques. We proposed an approach based on the concept of strong communities, or "community cores", and we showed the improvement made by our approach by applying it to real and artificial graphs. We also studied the structure of cores in random graphs and we showed that unlike classical community detection algorithms which can find communities in graphs with no intrinsic community structure, our approach clearly indicates the absence of community structure in random graphs and, in this way, allows to distinguish between random and real graphs. We also studied the evolution of cores in dynamical networks using a simple and controllable simulated dynamic and a real dynamic. We showed that cores are much more stable than communities obtained by current community detection techniques and our approach can overcome the disadvantages of stabilized methods that have been recently proposed
Cazabet, Rémy. "Détection de communautés dynamiques dans des réseaux temporels". Phd thesis, Université Paul Sabatier - Toulouse III, 2013. http://tel.archives-ouvertes.fr/tel-00874017.
Testo completoCanu, Maël. "Détection de communautés orientée sommet pour des réseaux mobiles opportunistes sociaux". Electronic Thesis or Diss., Paris 6, 2017. http://www.theses.fr/2017PA066378.
Testo completoOur research is in the field of complex network analysis and mining, specifically addressing the communit detection task, ie. algorithms aiming to uncover particularly dense subgraphs. We focus on the implementation of such an algorithm in a decentralised and distributed context : opportunistic MANET constituted of small wireless devices using peer-to-peer communication. To tackle the implementation constraints in such networks, we propose several methods designed according to the novel and trending vertex-centred paradigm, by combining Think-Like-a-Vertex graph processing with vertex-centred community detection methods based on leaders or seeds : they show specific properties allowing dsitributed implementations suiting the opportunistic MANET case. In this context, we first a global working principle and implement it in three different algorithms dedicated to three different configurations of community detection : the VOLCAN algorithm manages the classical disjoint community detection task in a static graph. We extend it with the LOCNeSs algorithm, that is dealing with overlapping communities which means that one vertex can belong to several communities. It adds more flexibility to the method and more significance to produced results. We also tackle the dynamic graphe case (graph evolving over time), addressed by the DynLOCNeSs algorithm.Each algorithm comes with a decentralised implementation and theoretical as well as experimental studies conducted both on real and synthetic benchmark data, allowing to evaluate the quality of the results and compare to existing state-of-the-art methods. Finally, we consider a special case of opportunistic decentralised MANET developped as a part of a research project about smart and communicating clothing. We formalise a task of path finding between smart t-shirts holders and propose a recommandation strategy using community structure, that we model and evaluate through an algorithm named SWAGG
Botterman, Hông-Lan. "Corrélations dans les graphes d'information hétérogène : prédiction et modélisation de liens à partir de méta-chemins". Electronic Thesis or Diss., Sorbonne université, 2020. http://www.theses.fr/2020SORUS083.
Testo completoMany entities, possibly of different natures, are linked by physical or virtual links, that may also be of different natures. Such data can be represented by a heterogeneous information network (HIN). In addition, there are often correlations between real-life entities or events. Once represented by suitable abstractions (such as HIN), these correlations can therefore be found in the HIN. Motivated by these considerations, this thesis investigates the effects of possible correlations between the links of an HIN on its structure. This present work aims at answering questions such as: are there indeed correlations between different types of links? If so, is it possible to quantify them? What do they mean? How can they be interpreted? Can these correlations be used to predict the occurrence of links? To model co-evolution dynamics? The examples studied can be divided into two categories. First, the use of correlations for the prediction of the links’ weight is studied. It is shown that correlations between links, and more specifically between paths, can be used to recover and, to some extent, predict the weight of other links of a specified type. Second, a link weight dynamics is considered. It is shown that link co-evolution can be used, for example, to define a model of attention between individuals and subjects. The preliminary results are in agreement with others in the literature, mainly related to models of opinion dynamics. Overall, this work illustrates the importance of correlations between the links of an HIN. In addition, it supports the general fact that different types of nodes and links abound in nature and that it could be important and instructive to take this diversity into account in order to understand the organization and functioning of a system
Mortelier, Alexis. "Οbservatοire de la tactique en (e-)spοrt cοllectif". Electronic Thesis or Diss., Normandie, 2024. http://www.theses.fr/2024NORMC245.
Testo completoThis thesis explores game dynamics and collective performance by alternating between analyses of traditional sports, such as handball, and e-sports, such as DotA2 and OverWatch. The aim is to segment the data processing process into several stages, each providing a specific understanding. By adopting a comparative approach between sport and e-sport, this work not only distinguishes the different stages of data processing, but also offers an overview of (e-)sport analysis. The first contribution is the development of techniques for representing handball matches using dynamic graphs, and the simplification of trajectories in DotA2 using geometric indices. The second contribution focuses on the definition and calculation of performance metrics, essential for machine learning. Expected goal (xG) models for handball and commitment factors in OverWatch have been developed as targets for algorithms. The third contribution is the creation of a tactical observatory dedicated to handball, and the study of geometric configurations in DotA2 that lead to key events. These analyses deepen our understanding of the tactics that influence the course of matches
Olivier, Pierre. "Modélisation et analyse du comportement dynamique d'un système d'électrolyse PEM soumis à des sollicitations intermittentes : Approche Bond Graph". Thesis, Lille 1, 2016. http://www.theses.fr/2016LIL10212/document.
Testo completoPEM Electrolysis is a technology which to enable to face two major challenges : (i) Fulfill the need of energy storage caused by the integration of intermittent energy sources on electricity networks; (ii) Cope with the growing need of carbon free hydrogen caused by the future market applications of hydrogen energy. These particular needs, regarding electrolysis technology development, involve an intermittent operating mode which impacts on the dynamic behavior of the system remain unknown. Modelling is a critical tool to understand these issues and provide a thorough analysis. State of the art of existing modelling works highlighted that only a few models take into account the dynamic of the whole system including Balance of Plant. Therefore a new dynamic and multiphysic model was developed under Bond Graph formalism. This graphical modelling formalism was selected especially thanks to its ability to represent any kind of power exchange in a unified way. The model enables to represent the whole system including balance of plant and associated control laws. It is validated on the dynamic behavior of an experimental device available in CEA. The model is then used in order to identify and understand the issues related to intermittent operation of a PEM electrolysis system. These issues are related to system efficiency, flexibility, reliability, safety and durability. Regarding these issues, some design changes are simulated and assessed. Finally, the Bond Graph model and its structural properties enable to perform diagnosis and monitorability analyses of a PEM electrolysis system
Gautier, Jacques. "GrAPHiSTUne approche d’analyse exploratoire pour l’identification des dynamiques des phénomènes spatio-temporels". Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAS025/document.
Testo completoDatasets allowing the description of spatio-temporal phenomena are becoming ever more numerous. These new data can be very different from those usually observed for studying spatio-temporal phenomena. An analysis through a hypothetico-deductive approach, like is mainly done in statistic and GIS domains, can ignore some unsuspected, but relevant, information about the dynamics of these spatio-temporal phenomena.It can be interesting then, to just present the data, to observe what they have to show, before analysing them. This is the principle of the exploratory data analysis: the process is to allow a user to freely explore data, through visual representations, in order to highlight unsuspected structures or relationships. Today, exploratory analysis is possible through visualization environments, which integrate different graphic or cartographic interactive representations.Visualization environments are mainly developed in an ad hoc manner, in the context of a particular thematic field. However, the constant appearance of new data encourages promoting analysis methods, which could be applied to several types of phenomena. According to the domain related to these phenomena, the analysis will be focused on different dynamics. Analysing a meteorological phenomenon, in a forecasting purpose, implies a focus on the cyclic recurrences of the phenomenon. Analysing the increase of a population, for the purpose of deciding public policies, implies an analysis of the phenomenon on a long-term, through different spatial areas.Our objective is to propose a method for the exploratory analysis of spatio-temporal phenomena and their dynamics, which would be independent of the topic. In order to achieve this, we propose a geovisualization environment, GrAPHiST (Géovisualisation pour l'Analyse des PHenomenes Spatio-Temporels; Geovisualization for spatio-temporal phenomena analysis), allowing the analysis of several dynamics, through different spatial and temporal (linear or cyclic) scales. Developing this environment implies to focus on how spatial changes are modelled, on the nature of the spatio-temporal dynamics we have to study, and on the visual and interactive tools, which allow the identification of these dynamics.So, the contributions of our research can be found at several levels:a generic modelling approach of spatio-temporal phenomena, in the form of event series;new graphical and interactive representation methods, which allow the searching and the identification of spatio-temporal dynamics, including: the introduction of interactive temporal diagrams, which allow the visual searching of cyclic recurrences in spatio-temporal data; the use of symbology rules, which allow the visualization of relationships between the spatial and temporal components of phenomena; new methods to represent aggregated closed events, which allow to identify structures in their spatio-temporal distribution;the formalization of an exploratory approach for the spatio-temporal dynamics analysis, divided into several scenarios, according to the purpose of the analysis.We validate our proposition by applying it to the analysis of several datasets. The objective is to verify the possibility to identify dynamics, related to linear or cyclic time, through the use of GrAPHiST, and to illustrate the generic aspect of the approach, as well as the analysis opportunities given by the environment
Jardin, Audrey. "Contribution à une méthodologie de dimensionnement des systèmes mécatroniques : analyse structurelle et couplage à l'optimisation dynamique". Phd thesis, INSA de Lyon, 2010. http://tel.archives-ouvertes.fr/tel-00597430.
Testo completoRen, Haolin. "Visualizing media with interactive multiplex networks". Thesis, Bordeaux, 2019. http://www.theses.fr/2019BORD0036/document.
Testo completoNowadays, information follows complex paths: information propagation involving on-line editors, 24-hour news providers and social medias following entangled paths acting on information content and perception. This thesis studies the adaptation of classical graph measurements to multiplex graphs, to build visualizations from several graphical representations of the networks, and to combine them (synchronized multi-view visualizations, hybrid representations, etc.). Emphasis is placed on the modes of interaction allowing to take in hand the multiplex nature (multilayer) of the networks. These representations and interactive manipulations are also based on the calculation of indicators specific to multiplex networks. The work is based on two main datasets: one is a 12-year archive of the Japanese public daily broadcast NHK News 7, from 2001 to 2013. Another lists the participants in the French TV/radio shows between 2010 and 2015. Two visualization systems based on a Web interface have been developed for multiplex network analysis, which we call "Visual Cloud" and "Laputa". In the Visual Cloud, we formally define a notion of similarity between concepts and groups of concepts that we call co-occurrence possibility (CP). According to this definition, we propose a hierarchical classification algorithm. We aggregate the layers in a multiplex network of documents, and integrate that hierarchy into an interactive word cloud. Here we improve the traditional word cloud layout algorithms so as to preserve the constraints on the concept hierarchy. The Laputa system is intended for the complex analysis of dense and multidimensional temporal networks. To do this, it associates a graph with a segmentation. The segmentation by communities, by attributes, or by time slices, forms views of this graph. In order to associate these views with the global whole, we use Sankey diagrams to reveal the evolution of the communities (diagrams that we have increased with a semantic zoom). This thesis allows us to browse three aspects of the most interesting aspects of the data miming and BigData applied to multimedia archives: The Volume since our archives are immense and reach orders of magnitude that are usually not practicable for the visualization; Velocity, because of the temporal nature of our data (by definition). The Variety that is a corollary of the richness of multimedia data and of all that one may wish to want to investigate. What we can retain from this thesis is that we met each of these three challenges by taking an answer in the form of a multiplex network analysis. These structures are always at the heart of our work, whether in the criteria for filtering edges using the Simmelian backbone algorithm, or in the superposition of time slices in the complex networks, or much more directly in the combinations of visual and textual semantic indices for which we extract hierarchies allowing our visualization
Guezzi, Abdelhak. "Modélisation, analyse de performance et commande des systèmes à événements discrets". Phd thesis, Université d'Angers, 2010. http://tel.archives-ouvertes.fr/tel-00730500.
Testo completoYazman, Atilla. "Modélisation des robots flexibles par les Bond-Graphs : application à l'analyse de leurs performances dynamiques". Paris 11, 1988. http://www.theses.fr/1988PA112106.
Testo completoCanu, Maël. "Détection de communautés orientée sommet pour des réseaux mobiles opportunistes sociaux". Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066378/document.
Testo completoOur research is in the field of complex network analysis and mining, specifically addressing the communit detection task, ie. algorithms aiming to uncover particularly dense subgraphs. We focus on the implementation of such an algorithm in a decentralised and distributed context : opportunistic MANET constituted of small wireless devices using peer-to-peer communication. To tackle the implementation constraints in such networks, we propose several methods designed according to the novel and trending vertex-centred paradigm, by combining Think-Like-a-Vertex graph processing with vertex-centred community detection methods based on leaders or seeds : they show specific properties allowing dsitributed implementations suiting the opportunistic MANET case. In this context, we first a global working principle and implement it in three different algorithms dedicated to three different configurations of community detection : the VOLCAN algorithm manages the classical disjoint community detection task in a static graph. We extend it with the LOCNeSs algorithm, that is dealing with overlapping communities which means that one vertex can belong to several communities. It adds more flexibility to the method and more significance to produced results. We also tackle the dynamic graphe case (graph evolving over time), addressed by the DynLOCNeSs algorithm.Each algorithm comes with a decentralised implementation and theoretical as well as experimental studies conducted both on real and synthetic benchmark data, allowing to evaluate the quality of the results and compare to existing state-of-the-art methods. Finally, we consider a special case of opportunistic decentralised MANET developped as a part of a research project about smart and communicating clothing. We formalise a task of path finding between smart t-shirts holders and propose a recommandation strategy using community structure, that we model and evaluate through an algorithm named SWAGG
Chatti, Nizar. "Contribution à la supervision des systèmes dynamiques à base des bond graph signés". Thesis, Lille 1, 2013. http://www.theses.fr/2013LIL10124/document.
Testo completoThe work presented in this paper deals with the diagnosis of single and multiple faults for continuous dynamic systems. It consists on developing a global diagnosis strategy for the operating modes management in both normal and abnormal situations. We first developed a new graphical formalism for dynamic system modelling. This formalism is emanating from the BG methodology and it is called Signed Bond Graph (SBG). This latter is easily understandable by a number of properties and definitions that we have established. The development of such formalism allows to use structural and causal properties of the BG and to expand its scope to include qualitative reasoning. Furthermore, we proposed a generic model for integrating functional Generic Component Models(GCM) and SBG models for the management of operating modes and reconfiguration conditions of an autonomous system using a finite automaton. Finally, we proposed a method for diagnosing both single and multiple faults using an abduction approach based on the faults propagation within the SBG by starting from a set of observations. The proposed methodology is validated by two different systems namely a proton exchange membrane fuel cell and an electromechanical system of an electric vehicle
Wilmet, Audrey. "Détection d'anomalies dans les flots de liens : combiner les caractéristiques structurelles et temporelles". Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS402.
Testo completoA link stream is a set of links {(t, u, v)} in which a triplet (t, u, v) models the interaction between two entities u and v at time t. In many situations, data result from the measurement of interactions between several million of entities over time and can thus be studied through the link stream's formalism. This is the case, for instance, of phone calls, email exchanges, money transfers, contacts between individuals, IP traffic, online shopping, and many more. The goal of this thesis is the detection of sets of abnormal links in a link stream. In a first part, we design a method that constructs different contexts, a context being a set of characteristics describing the circumstances of an anomaly. These contexts allow us to find unexpected behaviors that are relevant, according to several dimensions and perspectives. In a second part, we design a method to detect anomalies in heterogeneous distributions whose behavior is constant over time, by comparing a sequence of similar heterogeneous distributions. We apply our methodological tools to temporal interactions coming from retweets of Twitter and IP traffic of MAWI group
Lebert, Didier. "Essais sur la structure et la dynamique du capitalisme contemporain et de la division internationale du travail". Paris 1, 2010. http://www.theses.fr/2010PA010067.
Testo completoZreik, Rawya. "Analyse statistique des réseaux et applications aux sciences humaines". Thesis, Paris 1, 2016. http://www.theses.fr/2016PA01E061/document.
Testo completoOver the last two decades, network structure analysis has experienced rapid growth with its construction and its intervention in many fields, such as: communication networks, financial transaction networks, gene regulatory networks, disease transmission networks, mobile telephone networks. Social networks are now commonly used to represent the interactions between groups of people; for instance, ourselves, our professional colleagues, our friends and family, are often part of online networks, such as Facebook, Twitter, email. In a network, many factors can exert influence or make analyses easier to understand. Among these, we find two important ones: the time factor, and the network context. The former involves the evolution of connections between nodes over time. The network context can then be characterized by different types of information such as text messages (email, tweets, Facebook, posts, etc.) exchanged between nodes, categorical information on the nodes (age, gender, hobbies, status, etc.), interaction frequencies (e.g., number of emails sent or comments posted), and so on. Taking into consideration these factors can lead to the capture of increasingly complex and hidden information from the data. The aim of this thesis is to define new models for graphs which take into consideration the two factors mentioned above, in order to develop the analysis of network structure and allow extraction of the hidden information from the data. These models aim at clustering the vertices of a network depending on their connection profiles and network structures, which are either static or dynamically evolving. The starting point of this work is the stochastic block model, or SBM. This is a mixture model for graphs which was originally developed in social sciences. It assumes that the vertices of a network are spread over different classes, so that the probability of an edge between two vertices only depends on the classes they belong to
Manouvrier, Jean-François. "Méthode de décomposition pour résoudre des problèmes combinatoires sur les graphes". Compiègne, 1998. http://www.theses.fr/1998COMP1152.
Testo completoEl, Feki Mariem. "Analyse et synthèse de tolérance pour la conception et le dimensionnement des systèmes mécatroniques". Phd thesis, Ecole Centrale de Lyon, 2011. http://tel.archives-ouvertes.fr/tel-00688247.
Testo completoCorneli, Marco. "Dynamic stochastic block models, clustering and segmentation in dynamic graphs". Thesis, Paris 1, 2017. http://www.theses.fr/2017PA01E012/document.
Testo completoThis thesis focuses on the statistical analysis of dynamic graphs, both defined in discrete or continuous time. We introduce a new extension of the stochastic block model (SBM) for dynamic graphs. The proposed approach, called dSBM, adopts non homogeneous Poisson processes to model the interaction times between pairs of nodes in dynamic graphs, either in discrete or continuous time. The intensity functions of the processes only depend on the node clusters, in a block modelling perspective. Moreover, all the intensity functions share some regularity properties on hidden time intervals that need to be estimated. A recent estimation algorithm for SBM, based on the greedy maximization of an exact criterion (exact ICL) is adopted for inference and model selection in dSBM. Moreover, an exact algorithm for change point detection in time series, the "pruned exact linear time" (PELT) method is extended to deal with dynamic graph data modelled via dSBM. The approach we propose can be used for change point analysis in graph data. Finally, a further extension of dSBM is developed to analyse dynamic net- works with textual edges (like social networks, for instance). In this context, the graph edges are associated with documents exchanged between the corresponding vertices. The textual content of the documents can provide additional information about the dynamic graph topological structure. The new model we propose is called "dynamic stochastic topic block model" (dSTBM).Graphs are mathematical structures very suitable to model interactions between objects or actors of interest. Several real networks such as communication networks, financial transaction networks, mobile telephone networks and social networks (Facebook, Linkedin, etc.) can be modelled via graphs. When observing a network, the time variable comes into play in two different ways: we can study the time dates at which the interactions occur and/or the interaction time spans. This thesis only focuses on the first time dimension and each interaction is assumed to be instantaneous, for simplicity. Hence, the network evolution is given by the interaction time dates only. In this framework, graphs can be used in two different ways to model networks. Discrete time […] Continuous time […]. In this thesis both these perspectives are adopted, alternatively. We consider new unsupervised methods to cluster the vertices of a graph into groups of homogeneous connection profiles. In this manuscript, the node groups are assumed to be time invariant to avoid possible identifiability issues. Moreover, the approaches that we propose aim to detect structural changes in the way the node clusters interact with each other. The building block of this thesis is the stochastic block model (SBM), a probabilistic approach initially used in social sciences. The standard SBM assumes that the nodes of a graph belong to hidden (disjoint) clusters and that the probability of observing an edge between two nodes only depends on their clusters. Since no further assumption is made on the connection probabilities, SBM is a very flexible model able to detect different network topologies (hubs, stars, communities, etc.)
Jha, Mayank Shekhar. "Diagnostic et Pronostic de Systèmes Dynamiques Incertains dans un contexte Bond Graph". Thesis, Ecole centrale de Lille, 2015. http://www.theses.fr/2015ECLI0027/document.
Testo completoThis thesis develops the approaches for diagnostics and prognostics of uncertain dynamic systems in Bond Graph (BG) modeling framework. Firstly, properties of Interval Arithmetic (IA) and BG in Linear Fractional Transformation, are integrated for representation of parametric and measurement uncertainties on an uncertain BG model. Robust fault detection methodology is developed by utilizing the rules of IA for the generation of adaptive interval valued thresholds over the nominal residuals. The method is validated in real time on an uncertain and highly complex steam generator system.Secondly, a novel hybrid prognostic methodology is developed using BG derived Analytical Redundancy Relationships and Particle Filtering algorithms. Estimations of the current state of health of a system parameter and the associated hidden parameters are achieved in probabilistic terms. Prediction of the Remaining Useful Life (RUL) of the system parameter is also achieved in probabilistic terms. The associated uncertainties arising out of noisy measurements, environmental conditions etc. are effectively managed to produce a reliable prediction of RUL with suitable confidence bounds. The method is validated in real time on an uncertain mechatronic system.Thirdly, the prognostic methodology is validated and implemented on the electrical electro-chemical subsystem of an industrial Proton Exchange Membrane Fuel Cell. A BG of the latter is utilized which is suited for diagnostics and prognostics. The hybrid prognostic methodology is validated, involving real degradation data sets
Gonzalez, Vieyra Joel Abraham. "Estimation et Contrôle des Systèmes Dynamiques à Entrées Inconnues et Energies Renouvelables". Thesis, Ecole centrale de Lille, 2019. http://www.theses.fr/2019ECLI0012/document.
Testo completoNowadays, industrial processes must be efficient, particularly at the production level and/or energy consumption.This research work aims at improving the process efficiency by analysing the influences of disturbances on their behaviour, from the conception phase to the synthesis of controller/observer, in an integrated approach.The disturbance rejection problem is first introduced as well as different control laws allowing attenuate/reject these disturbances. A control law based on the concept of derivative state variable is presented and validated while applied as disturbance rejection.In order to reject the disturbance, different physical variables must be estimated, such as state variables, derivative state variables as disturbance variables. An unknown input observer based on the bond graph representation is recalled and extended in the multivariable case. It is the first theoretical contribution of this work.We thus compare the efficiency of different so-called «modern control laws» for the disturbance rejection problems by simulation with the Torsion-Bar system example. We analyse the efficiency of our approach. One extension to the Input-Output decoupling problem allows us to extend the disturbance rejection problem to other control law type in an integrated approach. At least, these techniques are applied on the real Torsion-Bar system and compared. We validate our approach.Since this work aims at analysing and developing efficient control laws for industrial processes, a simplified model of a hydroelectric plant is developed, in order to apply our results. A simplified bond graph model is validated with simulations
Crespelle, Christophe. "Représentations dynamiques de graphes". Phd thesis, Université Montpellier II - Sciences et Techniques du Languedoc, 2007. http://tel.archives-ouvertes.fr/tel-00402838.
Testo completoLes connexions entre les trois types de représentation précités sont exploitées pour la conception d'algorithmes de reconnaissance entièrement dynamiques pour les cographes orientés, les graphes de permutation et les graphes d'intervalles. Pour les cographes orientés, l'algorithme présenté est de complexité optimale, il traite les modifications de sommet en temps O(d), où d est le degré du sommet en question, et les modifications d'arête en temps constant. Les algorithmes pour les graphes de permutation et les graphes d'intervalles ont la même complexité : les modifications d'arête et de sommet sont traitées en temps O(n), où n est le nombre de sommets du graphe. Une des contributions du mémoire est de mettre en lumière des similarités très fortes entre les opérations d'ajout d'un sommet dans un graphe de permutation et dans un graphe d'intervalles.
L'approche mise en oeuvre dans ce mémoire est assez générale pour laisser entrevoir les mêmes possibilités algorithmiques pour d'autres classes de graphes définies géométriquement.
Venant, Fabienne. "Représentation et calcul dynamique du sens : exploration du lexique adjectival du français". Phd thesis, Ecole des Hautes Etudes en Sciences Sociales (EHESS), 2006. http://tel.archives-ouvertes.fr/tel-00067902.
Testo completoBougueroua, Sana. "Caractérisation de structures explorées dans les simulations de dynamique moléculaire". Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLV099/document.
Testo completoThis PhD is part of transdisciplinary works, combining graph theory and computational chemistry.In molecular dynamics simulations, a molecular system can adopt different conformations over time. Along a trajectory, one conformation or more can thus be explored. This depends on the simulation time and energy within the system. To get a good exploration of the molecular conformations, one must generate and analyse several trajectories (this can amount to thousands of trajectories). Our objective is to propose an automatic method that provides rapid and efficient analysis of the conformational dynamics explored over these trajectories. The trajectories of interest here are in cartesian coordinates of the atoms that constitute the molecular system, recorded at regular time intervals (time-steps). Each interval containing a set of positions is called a snapshot. At each snapshot, our developed algorithm uses geometric rules (distances, angles, etc.) to compute bonds (covalent bonds, hydrogen bonds and any other kind of intermolecular criterium) formed between atoms in order to get the mixed graph modelling one given conformation. Within our current definitions, a conformational change is characterized by either a change in the hydrogen bonds or in the covalent bonds. One choice or the other depends on the underlying physics and chemistry of interest. The proposed algorithm provides all conformations explored along one or several trajectories, the period of time for the existence of each one of these conformations, and also provides the graph of transitions that shows all conformational changes that have been observed during the trajectories. A user-friendly interface has been developed, that can de distributed freely.Our proposed algorithm for analysing the trajectories of molecular dynamics simulations has been tested on three kinds of gas phase molecular systems (peptides, ionic clusters). This model can be easily adapted and applied to any other molecular systems as well as to condensed matter systems, with little effort. Although the theoretical complexity of the algorithm is exponential (isomorphism tests), results have shown that the algorithm is rapid.We have also worked on computationally low cost graph methods that can be applied in order to pre-characterize specific conformations/points on a potential energy surface (it describes the energy of a system in terms of positions of the atoms). These points are the minima on the surface, representing the most stable conformations of a molecular system, and the maxima on that surface, representing transition states between two conformers. Our developed methods and algorithms aim at getting these specific points, without the prerequisite knowledge/calculation of the potential energy surface by quantum chemistry methods (or even by classical representations). By avoiding an explicit calculation of the potential energy surface by quantum chemistry methods, one saves computational time and effort. We have proposed an alternative method using ad doc measures based on properties of the graphs (already used in the first part of the PhD), without any knowledge of energy and/or molecular calculations. These measures allow getting the possible conformations with a realistic energy classification, as well as transition states, at very low computational cost. The algorithm has been tested on gas phase peptides
Desmier, Elise. "Co-evolution pattern mining in dynamic attributed graphs". Thesis, Lyon, INSA, 2014. http://www.theses.fr/2014ISAL0071/document.
Testo completoThis thesis was conducted within the project ANR FOSTER, ``Spatio-Temporal Data Mining: application to the understanding and monitoring of erosion'' (ANR-2010-COSI-012-02, 2011-2014). In this context, we are interested in the modeling of spatio- temporal data in enriched graphs so that computation of patterns on such data can be used to formulate interesting hypotheses about phenomena to understand. Specifically, we are working on pattern mining in relational graphs (each vertex is uniquely identified), attributed (each vertex of the graph is described by numerical attributes) and dynamic (attribute values and relations between vertices may change over time). We propose a new pattern domain that has been called co-evolution patterns. These are trisets of vertices, times and signed attributes, i.e., attributes associated with a trend (increasing or decreasing). The interest of these patterns is to describe a subset of the data that has a specific behaviour and a priori interesting to conduct non-trivial analysis. For this purpose, we define two types of constraints, a constraint on the structure of the graph and a constraint on the co-evolution of the value worn by vertices attributes. To confirm the specificity of the pattern with regard to the rest of the data, we define three measures of density that tend to answer to three questions. How similar is the behaviour of the vertices outside the co-evolution pattern to the ones inside it? What is the behaviour of the pattern over time, does it appear suddenly? Does the vertices of the pattern behave similarly only on the attributes of the pattern or even outside? We propose the use of a hierarchy of attributes as an a priori knowledge of the user to obtain more general patterns and we adapt the set of constraints to the use of this hierarchy. Finally, to simplify the use of the algorithm by the user by reducing the number of thresholds to be set and to extract only all the most interesting patterns, we use the concept of ``skyline'' reintroduced recently in the domain of data mining. We propose three constraint-based algorithms, called MINTAG, H-MINTAG and Sky-H-MINTAG, that are complete to extract the set of all patterns that meet the different constraints. These algorithms are based on constraints, i.e., they use the anti-monotonicity and piecewise monotonicity/anti-monotonicity properties to prune the search space and make the computation feasible in practical contexts. To validate our method, we experiment on several sets of data (graphs) created from real-world data
Parmentier, Frédéric. "Modélisation et prédiction de la dynamique moléculaire de la maladie de Huntington par la théorie des graphes au travers des modèles et des espèces, et priorisation de cibles thérapeutiques". Thesis, Sorbonne Paris Cité, 2015. http://www.theses.fr/2015PA05T030.
Testo completoHuntington’s disease is a hereditary neurodegenerative disease that has become a model to understand physiopathological mechanisms associated to misfolded proteins that ocurs in brain diseases. Despite exciting findings that have uncover pathological mechanisms occurring in this disease and that might also be relevant to Alzheimer’s disease and Parkinson’s disease, we still do not know yet which are the mechanisms and molecular profiles that rule the dynamic of neurodegenerative processes in Huntington’s disease. Also, we do not understand clearly how the brain resist over such a long time to misfolded proteins, which suggest that the toxicity of these proteins is mild, and that the brain have exceptional compensation capacities. My work is based on the hypothesis that integration of ‘omics’ data from models that depicts various stages of the disease might be able to give us clues to answer these questions. Within this framework, the use of network biology and graph theory concepts seems particularly well suited to help us integrate heterogeneous data across models and species. So far, the outcome of my work suggest that early, pre-symptomatic alterations of signaling pathways and cellular maintenance processes, and persistency and worthening of these phenomenon are at the basis of physiopathological processes that lead to neuronal dysfunction and death. These results might allow to prioritize targets and formulate new hypotheses that are interesting to further study and test experimentally. To conclude, this work shall have a fundamental and translational impact to the field of Huntington’s disease, by pinpointing methods and hypotheses that could be valuable in a therapeutic perspective
Cheng, Zhi. "Mining recurrent patterns in a dynamic attributed Graph. : Application on aquaculture pond monitoring by satellite images". Thesis, Nouvelle Calédonie, 2018. http://www.theses.fr/2018NCAL0004.
Testo completoIn this thesis, we are interested in analyzing spatio-temporal data. Numerous algorithms have been developed to extract local models (also called "patterns") such as sequential patterns or dynamic subgraphs. However, these approaches suffer from severa!limitations when dealing with complex spatio-temporal phenomena. These pattern demains do not consider all possible spatio-temporal interactions or only consider limited information about studied objects. For example, sequential pattern mining methods focus on temporal evolutions without considering spatial ones. Besicles, most of graph mining algorithms study labeled graphs. They only consider one attribute per vertex instead of all object's characteristics. In our work, we propose to study dynamic attributed graph, because they provide a richer representation of spatio-temporal phenomena. Extraction of patterns in dynamic attributed graph is a particularly complex task because graph structure, vertices and attributes associated with each vertex can change over time. For this purpose, we define a new pattern domain called recurrent patterns. These patterns, which are sequences of connected ubgraph, œpreent recurrent evolutions of subsets of attributes associated to vertices. To extract these patterns, we develop a new algorithm, RPMiner, using an original strategy based on successive intersections of connected components. We use severa! constraints to reduce the search space and make the computation feasible. Experimental study on both syndetic and two real-world datasets (DBLP dataset and Domestic US Flight dataset) show the genericity of our approach, the interest of extracted patterns and the efficiency of our algorithm. We also do an in-depth experimental evaluation of our approach on the INDESO project data (aquaculture pond monitoring in lndonesia by satellite images). A complete KDD process has been developed: from pre-processing of data to visualization and interpretation of results. It aims to better understand farming practices for sustainable development of these coastal resources in Indonesia.This process is firstly based on an automatic and robust method to extract aquaculture ponds from low contrast satellite images. Next, this process extracts frequent patterns to highlight sorne farming practices. For this, we have firstly applied a sequential pattern mining to analyze temporal evolutions of aquaculture ponds and to understand farming practices. In parallel, we also apply our algorithm, RPMiner, which considers both spatial and temporal aspects. Extracted patterns were interpreted by aquaculture experts. Results confirm severa!practices and highlight ethers
Dion, Dominique. "Dynamique d'évolution de graphes de cooccurrences lexicales : application à l'analyse de comptes rendus en prévention spécialisée entre 1972 et 2010". Phd thesis, Université Victor Segalen - Bordeaux II, 2012. http://tel.archives-ouvertes.fr/tel-00842790.
Testo completoDuvignau, Romaric. "Maintenance et simulation de graphes aléatoires dynamiques". Thesis, Bordeaux, 2015. http://www.theses.fr/2015BORD0177/document.
Testo completoWe study the problem of maintaining a given distribution of randomgraphs under an arbitrary sequence of vertex insertions and deletions. Keeping inmind our objective to model the evolution of dynamic logical networks, we work ina local model where we do not have direct access to the list of all vertices. Instead,we assume access to a global primitive that returns a random vertex, chosen uniformlyfrom the whole vertex set. The maintenance problem has been explored onseveral simple random graph models (Erdos–Rényi random graphs, pairing modelbased random graphs, uniform k-out graphs). For each model, one or several updatealgorithms for the maintenance task have been described and analyzed ; the mostelaborate of them are asymptically optimal. The maintenance task rise several simulationissues linked to our distributed context. In particular, we have focused onmaintenability of random graph distributions and simulability of families of probabilitydistributions over integers in our local random model. Special attention hasbeen paid to efficient simulation of particular distributions we were interested in(certain binomial distributions). The latter has been obtained through the use ofproperties of a new generation tree for permutations, which has been introducedalong the way
Vernet, Mathilde. "Modèles et algorithmes pour les graphes dynamiques". Thesis, Normandie, 2020. http://www.theses.fr/2020NORMLH12.
Testo completoGraph problems have been widely studied in the case of static graphs. However, these graphs do not allow a time dimension to be considered, even though time is an important variable for the situations to model. Dynamic graphs make it possible to model evolution over time. This is a reason to wonder about graph problems in a dynamic context. First, it is necessary to define the most appropriate dynamic graphs model and the precise problem on those graphs. When the problem cannot be efficiently solved directly using known static graph methods, an algorithm specific to dynamic graphs must be designed and analyzed theoretically and practically.With that approach, this thesis' objective is to study graph problems' extensions to dynamic graphs. This works deals with several graph problems in a dynamic context by focusing on algorithmic aspects and without considering application domains
Durbec, Amélia. "Dynamiques causales de graphes réversibles et quantiques". Electronic Thesis or Diss., Aix-Marseille, 2022. http://www.theses.fr/2022AIXM0459.
Testo completoCausal graph dynamics are a twofold extension of cellular automata: the underlying grid is extended to an arbitrary graph of bounded degree and the graph itself can evolve in time.In the reversible regime, we prove that causal graph dynamics can be reversible while creating/destroying vertices, through three different models that we prove to be equivalent.Based on these results, we exhibit causal dynamics that are both reversible and increasing in space, which brings new insights into the compatibility between the time arrow and reversibility. We define a notion of graph subshifts, which can be used to study causal dynamics of graphs by unifying temporal and spatial dimensions, in the same way that 1D cellular automata can be studied with 2D subshifts of finite type.In the quantum regime, our first contribution is to provide a rigorous definition of state space. A notable question was whether vertex names are necessary; we prove they are indeed necessary in order to prevent faster-than-light signaling. We also point out that renaming on graphs is the natively discrete analog of coordinate changes
Maag, Maria Coralia Laura. "Apprentissage automatique de fonctions d'anonymisation pour les graphes et les graphes dynamiques". Thesis, Paris 6, 2015. http://www.theses.fr/2015PA066050/document.
Testo completoData privacy is a major problem that has to be considered before releasing datasets to the public or even to a partner company that would compute statistics or make a deep analysis of these data. Privacy is insured by performing data anonymization as required by legislation. In this context, many different anonymization techniques have been proposed in the literature. These techniques are difficult to use in a general context where attacks can be of different types, and where measures are not known to the anonymizer. Generic methods able to adapt to different situations become desirable. We are addressing the problem of privacy related to graph data which needs, for different reasons, to be publicly made available. This corresponds to the anonymized graph data publishing problem. We are placing from the perspective of an anonymizer not having access to the methods used to analyze the data. A generic methodology is proposed based on machine learning to obtain directly an anonymization function from a set of training data so as to optimize a tradeoff between privacy risk and utility loss. The method thus allows one to get a good anonymization procedure for any kind of attacks, and any characteristic in a given set. The methodology is instantiated for simple graphs and complex timestamped graphs. A tool has been developed implementing the method and has been experimented with success on real anonymized datasets coming from Twitter, Enron or Amazon. Results are compared with baseline and it is showed that the proposed method is generic and can automatically adapt itself to different anonymization contexts
Maag, Maria Coralia Laura. "Apprentissage automatique de fonctions d'anonymisation pour les graphes et les graphes dynamiques". Electronic Thesis or Diss., Paris 6, 2015. http://www.theses.fr/2015PA066050.
Testo completoData privacy is a major problem that has to be considered before releasing datasets to the public or even to a partner company that would compute statistics or make a deep analysis of these data. Privacy is insured by performing data anonymization as required by legislation. In this context, many different anonymization techniques have been proposed in the literature. These techniques are difficult to use in a general context where attacks can be of different types, and where measures are not known to the anonymizer. Generic methods able to adapt to different situations become desirable. We are addressing the problem of privacy related to graph data which needs, for different reasons, to be publicly made available. This corresponds to the anonymized graph data publishing problem. We are placing from the perspective of an anonymizer not having access to the methods used to analyze the data. A generic methodology is proposed based on machine learning to obtain directly an anonymization function from a set of training data so as to optimize a tradeoff between privacy risk and utility loss. The method thus allows one to get a good anonymization procedure for any kind of attacks, and any characteristic in a given set. The methodology is instantiated for simple graphs and complex timestamped graphs. A tool has been developed implementing the method and has been experimented with success on real anonymized datasets coming from Twitter, Enron or Amazon. Results are compared with baseline and it is showed that the proposed method is generic and can automatically adapt itself to different anonymization contexts
Loubier, Éloïse. "Analyse et visualisation de données relationnelles par morphing de graphe prenant en compte la dimension temporelle". Toulouse 3, 2009. http://thesesups.ups-tlse.fr/2264/.
Testo completoWith word wide exchanges, companies must face increasingly strong competition and masses of information flows. They have to remain continuously informed about innovations, competition strategies and markets and at the same time they have to keep the control of their environment. The Internet development and globalization reinforced this requirement and on the other hand provided means to collect information. Once summarized and synthesized, information generally is under a relational form. To analyze such a data, graph visualization brings a relevant mean to users to interpret a form of knowledge which would have been difficult to understand otherwise. The research we have carried out results in designing graphical techniques that allow understanding human activities, their interactions but also their evolution, from the decisional point of view. We also designed a tool that combines ease of use and analysis precision. It is based on two types of complementary visualizations: statics and dynamics. The static aspect of our visualization model rests on a representation space in which the precepts of the graph theory are applied. Specific semiologies such as the choice of representation forms, granularity, and significant colors allow better and precise visualizations of the data set. The user being a core component of our model, our work rests on the specification of new types of functionalities, which support the detection and the analysis of graph structures. We propose algorithms which make it possible to target the role of the data within the structure, to analyze their environment, such as the filtering tool, the k-core, and the transitivity, to go back to the documents, and to give focus on the structural specificities. One of the main characteristics of strategic data is their strong evolution. However the statistical analysis does not make it possible to study this component, to anticipate the incurred risks, to identify the origin of a trend, and to observe the actors or terms having a decisive role in the evolution structures. With regard to dynamic graphs, our major contribution is to represent relational and temporal data at the same time; which is called graph morphing. The objective is to emphasize the significant tendencies considering the representation of a graph that includes all the periods and then by carrying out an animation between successive visualizations of the graphs attached to each period. This process makes it possible to identify structures or events, to locate them temporally, and to make a predictive reading of it. Thus our contribution allows the representation of advanced information and more precisely the identification, the analysis, and the restitution of the underlying strategic structures which connect the actors of a domain, the key words, and the concepts they use; this considering the evolution feature
Jarkass, Iman. "Reconnaissance de l'état d'un système dynamique à l'aide d'un réseau de Petri crédibiliste". Compiègne, 1998. http://www.theses.fr/1998COMP1136.
Testo completoWade, Ahmed mouhamadou. "Complexité de l'exploration par agent mobile des graphes dynamiques". Thesis, Bordeaux, 2014. http://www.theses.fr/2014BORD0484/document.
Testo completoIn this thesis, we study the complexity of the problem of exploration by a mobileagent in dynamic graphs. A mobile entity (called agent) moving in a dynamic graph hasto traverse/visit each of its vertices at least once. This fundamental problem in computatingby mobile agents has been well-studied in static graphs since the original paper ofClaude Shannon. However, for highly dynamic graphs, only the case of periodic dynamicgraphs has been studied. We study this problem in two families of dynamic graphs,periodically-varying graphs (PV-graphs) and T-interval-connected dynamic graphs. Theobtained results improve the existing results and give optimal bounds on the studiedproblems
Martiel, Simon. "Approches informatique et mathématique des dynamiques causales de graphes". Thesis, Nice, 2015. http://www.theses.fr/2015NICE4043/document.
Testo completoCellular Automata constitute one of the most established model of discrete physical transformations that accounts for euclidean space. They implement three fundamental symmetries of physics: causality, homogeneity and finite density of information. Even though their origins lies in physics, they are widely used to model spatially distributed computation (self-replicating machines, synchronization problems,...), as well as a great variety of multi-agents phenomena (traffic jams, demographics,...). While being one of the most studied model of distributed computation, their rigidity forbids any trivial extension toward time-varying topology, which is a fundamental requirement when it comes to modelling phenomena in biology, sociology or physics: for instance when looking for a discrete formulation of general relativity. Causal graph dynamics generalize cellular automata to arbitrary, bounded degree, time-varying graphs. In this work, we generalize the fundamental structure results of cellular automata for this type of transformations. We endow our graphs with a compact metric space structure, and follow two approaches. An axiomatic approach based on the notions of continuity and shift-invariance, and a constructive approach, where a local rule is applied synchronously on every vertex of the graph. Compactness allows us to show the equivalence of these two definitions, extending the famous result of Curtis-Hedlund-Lyndon’s theorem. Another physics-inspired symmetry is then added to the model, namely reversibility