Analyse formelle de concepts et règles d'association pour la gestion de contexte dans des environnements ubiquitaires

National audienceMon sujet de recherche vise à gérer et analyser les informations liées au contexte d'un utilisateur, disponibles grâce à l'informatique ubiquitaire. D'énormes volumes de données très diverses sont en effet collectés par des capteurs, fournissant par exemple des indicateurs sur la localisation géographique d'un individu, les conditions météorologiques, etc. Les collectes de données de ce type se multiplient, par exemple dans le cadre des villes intelligentes. Ce contexte " environnemental " peut être enrichi d'autres informations relatives aux utilisateurs, par exemple, leurs activités. Ceux-ci peuvent aussi être eux-mêmes fournisseurs d'indicateurs lorsqu'ils renseignent leur profil. L'objectif de mes travaux est de pouvoir prédire ses actions futures en fonction des évolutions de ce contexte ou de lui faire des recommandations

A Comparative Study of Domestic and Hospital Environmental Microbial Populations in Al-Ain (UAE)

This is the first attempt to estimate biological indoor pollution in the environment of AI-Ain city. The numbers and types of bacteria and fungi in the air and on the surfaces were measured in AI-Ain hospital and three different types of domestic environments. Five different types of wards at AI-Ain hospital, medical, surgical, pediatrics, operating theater, and intensive care unit were studied. Their estimated indoor bioaerosols were compared to indoor bioaerosols in three types of dwelling houses, very good, average, and poor quality houses in AI-Ain city. A bacteriological mechanical air sampler, MK2 (Casella London) was used in this study. The result of this study showed that the same groups of bacteria and fungi isolated from the hospital environment were also found in domestic air samples. The highest number of bacteria in the hospital was found in the pediatric and female medical wards while the lowest were in the operating theater. The number of bacteria in the domestic environment was related to the type of housing; the higher the quality of house the lower the number of micro-organisms. Pathogenic and human related micro-organisms were found to be more prevalent in a hospital environment than in the domestic environment. In general the hospital air microbial counts were comparable to very good quality houses. The commonest species of fungi found in both environments were AsperigiIlus niger. Surface samples in hospital and homes showed that surface micro-organisms originated from air contaminants. A comparison of hospital and domestic bacterial sensitivity was carried out using coagulase negative Staphylococci (CNS). These were also compared to the patients\u27n CNS. The sensitivity pattern of CNS indicated that the environment or the source of the microbes had some effect upon the micro-organisms. Domestic airborne CNS were very sensitive to nearly all the antibiotics tested while patients harbored the most resistant CNS with hospital airborne CNS falling in between. Hospital airborne agents would seem to be a mixture of patients\u27 strains and the environmental strains possibly brought in by visitors to the hospital

Towards an Automatic Extraction of Smartphone Users' Contextual Behaviors

International audienceThis paper presents a new method for automatically extracting smartphone users' contextual behaviors from the digital traces collected during their interactions with their devices. Our goal is in particular to understand the impact of users' context (e.g., location, time, environment, etc.) on the applications they run on their smartphones. We propose a methodology to analyze digital traces and to automatically identify the significant information that characterizes users' behaviors. In earlier work, we have used Formal Concept Analysis and Galois lattices to extract relevant knowledge from heterogeneous and complex contextual data; however, the interpretation of the obtained Galois lattices was performed manually. In this article, we aim at automating this interpretation process, through the provision of original metrics. Therefore our methodology returns relevant information without requiring any expertise in data analysis. We illustrate our contribution on real data collected from volunteer users

Unified and Conceptual Context Analysis in Ubiquitous Environments

International audienceThis article presents an original approach for the analysis of context information in ubiquitous environments. Large volumes of heterogeneous data are now collected, such as location, temperature, etc. This "environmental" context may be enriched by data related to users, e.g., their activities or applications. We propose a unified analysis and correlation of all these dimensions of context in order to measure their impact on user activities. Formal Concept Analysis and association rules are used to discover non-trivial relationships between context elements and activities, which, otherwise, could seem independent. Our goal is to make an optimal use of available data in order to understand user behavior and eventually make recommendations. In this paper, we describe our general methodology for context analysis and we illustrate it on an experiment conducted on real data collected by a capture system. Thanks to this methodology, it is possible to identify correlation between context elements and user applications, making possible to recommend such applications for user in similar situations

Refinement Strategies for Correlating Context and User Behavior in Pervasive Information Systems

International audienceLarge amounts of traces can be collected by Pervasive Information Systems, reflecting user's actions and the context in which these actions have been performed (location, date, time, network connection, etc.). This article proposes refinement strategies with different frequency measurements on contextual elements in order to better analyze the impact of these elements on the user's behavior. These strategies are based on data mining and Formal Concept Analysis and used to refine input data in order to identify the context elements that have a strong impact on user behaviors. We go further on context analysis by cognizing FCA with semantic distance measures calculated based on a context ontology. The proposed context analysis is further on evaluated in experiments with real data. The novelties of this work lies on these refinement strategies which can lead to a better understanding of context impact. Such understanding represents an important step towards personalization and recommendation features

Forum Jeunes Chercheurs à Inforsid 2014

Le Forum Jeunes Chercheurs a été organisé lors du congrès Inforsid 2014 à Lyon. Il a accueilli 17 doctorants de première ou deuxième année travaillant dans le domaine des systèmes d’information. Ils ont rédigé un article et présenté leurs travaux lors d’une session plénière du congrès. Cet article coordonné par Guillaume Cabanac (en qualité d’organisateur du Forum) présente une sélection des quatre meilleures contributions au forum

Adverse effects in wild fish living downstream from pharmaceutical manufacture discharges

International audienceA set of biochemical and histological responses was measured in wild gudgeon collected upstream and downstream of urban and pharmaceutical manufacture effluents. These individual end-points were associated to fish assemblage characterisation. Responses of biotransformation enzymes, neurotoxicity and endocrine disruption biomarkers revealed contamination of investigated stream by a mixture of pollutants. Fish from sampled sites downstream of the industrial effluent exhibited also strong signs of endocrine disruption including vitellogenin induction, intersex and male-biased sex-ratio. These individual effects were associated to a decrease of density and a lack of sensitive fish species. This evidence supports the hypothesis that pharmaceutical compounds discharged in stream are involved in recorded endocrine disruption effects and fish population disturbances and threaten disappearance of resident fish species. Overall, this study gives argument for the utilisation of an effect-based monitoring approach to assess impacts of pharmaceutical manufacture discharges on wild fish populations

Aide à l'utilisation et à l'exploitation de l'analyse de concepts formels pour des non-spécialistes de l'analyse des données

Many data analysis techniques have been developed to extract knowledge from the data. The two traditional approaches are descriptive analysis and predictive. We focus in this thesis on descriptive data analysis, and in particular on Formal Concepts Analysis (FCA). This approach builds overlapping clusters (called formal concepts) whose meaning is explicit. There is a partial order relationship between the formal concepts resulting from FCA, which are organized in a mathematical structure called a Galois lattice. Despite its advantages, FCA is poorly accessible to users who are not experts in data analysis. Although graphical representations of Galois lattices exist, their interpretation remains difficult for large data. Moreover, the construction of FCA input data, called formal context, can be tricky. For this, we have proposed a methodology for Galois lattice interpretation based on a set of simple metrics, the results of which are presented in a visual form as intuitive as possible. We have also developed strategies for constructing formal contexts that not only remain as close to the initial data as possible, but also take into consideration the user's needs in terms of information retrieval.De nombreuses approches ont été élaborées pour extraire des connaissances à partir des données. On distingue traditionnellement l’analyse descriptive et l’analyse prédictive. Nous nous focalisons dans cette thèse sur l’analyse descriptive des données et plus particulièrement sur l’Analyse de Concepts Formels (ACF), qui permet de construire des clusters recouvrants (appelés concepts formels) dont la signification est explicite. Il existe une relation d’ordre partiel entre les concepts formels résultant de l’ACF, qui sont organisés en une structure mathématique appelée treillis de Galois. Malgré ses nombreux avantages, l’ACF est peu accessible à des utilisateurs non experts de l’analyse de données. En effet, malgré les représentations graphiques des treillis de Galois, ceux-ci restent difficiles à interpréter, notamment lorsque les données sont volumineuses. De plus, la construction des données d’entrée de l’ACF sous la forme d’un contexte formel peut être délicate. Pour cela, nous avons proposé une méthodologie d’interprétation des treillis de Galois reposant sur un ensemble de métriques simples, dont les résultats sont présentés sous une forme visuelle aussi intuitive que possible. Nous avons également développé des stratégies pour construire des contextes formels qui, non seulement, dénaturent le moins possible les données initiales, mais permettent aussi de tenir compte des besoins de l’utilisateur en termes de recherche d’information