Suchergebnisse

Dans le domaine de l'action sociale des régimes de retraite Agirc et Arrco, les partenaires sociaux ont choisi de soutenir une action toujours innovante à ce jour : la prévention globale, couvrant le champ médico-psycho-social, pour un vieillissement « réussi » des populations âgées, voire très âgées. Il s'agit de l'un des axes prioritaires de l'action sociale de la retraite complémentaire, qui cible également l'accompagnement de la perte d'autonomie à domicile ou l'entrée en établissement d'hébergement.

Résumé Pour faire face aux grandes évolutions démographiques, le plan d'action des fédérations Agirc et Arrco 2009-2013 se déploie dans trois grandes orientations, communes à toutes les institutions de retraite complémentaires (IRC). La première concerne le développement de la prévention. La seconde travaille à prolonger l'autonomie des personnes âgées et handicapées au domicile. La dernière accompagne la perte d'autonomie au sein des structures collectives. C'est dans le cadre de la seconde orientation que la direction de l'action sociale a conduit une étude sécurité habitat où les nouvelles technologiques ont toute leur place. Bilan contrasté et instructif de la compréhension des besoins par les différents acteurs.

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Das Auftauchen der elektronischen Datenverarbeitung modifiziert die Arbeitspraxis und bringt tendenziell die sozialen Formen der Arbeitsteilung durcheinander. Der Artikel stutzt sich auf die Analyse der täglichen Arbeitspraxis bei der französischen Zeitung Ouest-France auf, um zu zeigen, wie trotz des Willens der Geschäftsleitung, die verschiedenen Berufe einander anzunähern, die Beschäftigten dahin gebracht werden, untereinander berufliche Trennwände zu errichten. So erlangen die Drucker mit derBeherrschung der EDV-Einrichtungen verbundeneKompetenzen. Um sodann fur sich den Anspruch zuerheben, die einzigen Garanten einer in der Berufskultur der « Buchfachleute » verankerten beruflichen Qualität zu sein. Sie streben außerdem danach, die Erhaltung ihres Berufes sicherzustellen, mit welcher Technik er auch immer ausgeubt werde. Dem gegeniiber weigern sich die Journalisten, denen dasKompetenzideal eher mit der intellektuellen Dimension und weniger mit der technischen Ebene ihres Berufsverbunden ist, sich die mit der Verwendung der EDV verknupften Fachkenntnisse anzueignen.

International audience ; Graph databases (NoSQL oriented graph databases) provide the ability to manage highly connected data and complex database queries along with the native graph-storage and processing. A property graph in a NoSQL graph engine is a labeled directed graph composed of nodes connected through edges with a set of attributes or properties in the form of (key : value) pairs. It facilitates to represent the data and knowledge that are in form of graphs. Practical applications of graph database systems have been seen in social networks, recommendation systems, fraud detection, and data journalism, as in the case for panama papers. Often, we face the issue of missing data in such kind of systems. In particular, these semi-structured NoSQL databases lead to a situation where some attributes (properties) are filled-in while other ones are not available, either because they exist but are missing (for instance the age of a person that is unknown) or because they are not applicable for a particular case (for instance the year of military service for a girl in countries where it is mandatory only for boys). Therefore, some keys can be provided for some nodes and not for other ones. In such a scenario, when we want to extract knowledge from these new generation database systems, we face the problem of missing data that arises need for analyzing them. Some approaches have been proposed to replace missing values so as to be able to apply data mining techniques. However, we argue that it is not relevant to consider such approaches because they may introduce biases or errors. In our work, we focus on the extraction of gradual patterns from property graphs that provide end-users with tools for mining correlations in the data when there exist missing values. Our approach requires first to define gradual patterns in the context of NoSQL property graph and then to extend existing algorithms so as to treat the missing values, because anti-monotonicity of the support can not be considered anymore in a simple manner. ...

International audience ; Graph databases (NoSQL oriented graph databases) provide the ability to manage highly connected data and complex database queries along with the native graph-storage and processing. A property graph in a NoSQL graph engine is a labeled directed graph composed of nodes connected through edges with a set of attributes or properties in the form of (key : value) pairs. It facilitates to represent the data and knowledge that are in form of graphs. Practical applications of graph database systems have been seen in social networks, recommendation systems, fraud detection, and data journalism, as in the case for panama papers. Often, we face the issue of missing data in such kind of systems. In particular, these semi-structured NoSQL databases lead to a situation where some attributes (properties) are filled-in while other ones are not available, either because they exist but are missing (for instance the age of a person that is unknown) or because they are not applicable for a particular case (for instance the year of military service for a girl in countries where it is mandatory only for boys). Therefore, some keys can be provided for some nodes and not for other ones. In such a scenario, when we want to extract knowledge from these new generation database systems, we face the problem of missing data that arises need for analyzing them. Some approaches have been proposed to replace missing values so as to be able to apply data mining techniques. However, we argue that it is not relevant to consider such approaches because they may introduce biases or errors. In our work, we focus on the extraction of gradual patterns from property graphs that provide end-users with tools for mining correlations in the data when there exist missing values. Our approach requires first to define gradual patterns in the context of NoSQL property graph and then to extend existing algorithms so as to treat the missing values, because anti-monotonicity of the support can not be considered anymore in a simple manner. ...

International audience ; Graph databases (NoSQL oriented graph databases) provide the ability to manage highly connected data and complex database queries along with the native graph-storage and processing. A property graph in a NoSQL graph engine is a labeled directed graph composed of nodes connected through edges with a set of attributes or properties in the form of (key : value) pairs. It facilitates to represent the data and knowledge that are in form of graphs. Practical applications of graph database systems have been seen in social networks, recommendation systems, fraud detection, and data journalism, as in the case for panama papers. Often, we face the issue of missing data in such kind of systems. In particular, these semi-structured NoSQL databases lead to a situation where some attributes (properties) are filled-in while other ones are not available, either because they exist but are missing (for instance the age of a person that is unknown) or because they are not applicable for a particular case (for instance the year of military service for a girl in countries where it is mandatory only for boys). Therefore, some keys can be provided for some nodes and not for other ones. In such a scenario, when we want to extract knowledge from these new generation database systems, we face the problem of missing data that arises need for analyzing them. Some approaches have been proposed to replace missing values so as to be able to apply data mining techniques. However, we argue that it is not relevant to consider such approaches because they may introduce biases or errors. In our work, we focus on the extraction of gradual patterns from property graphs that provide end-users with tools for mining correlations in the data when there exist missing values. Our approach requires first to define gradual patterns in the context of NoSQL property graph and then to extend existing algorithms so as to treat the missing values, because anti-monotonicity of the support can not be considered anymore in a simple manner. Thus, we introduce a novel approach for mining gradual patterns in the presence of missing values and we test it on real and synthetic data.

International audience ; Graph databases (NoSQL oriented graph databases) provide the ability to manage highly connected data and complex database queries along with the native graph-storage and processing. A property graph in a NoSQL graph engine is a labeled directed graph composed of nodes connected through edges with a set of attributes or properties in the form of (key : value) pairs. It facilitates to represent the data and knowledge that are in form of graphs. Practical applications of graph database systems have been seen in social networks, recommendation systems, fraud detection, and data journalism, as in the case for panama papers. Often, we face the issue of missing data in such kind of systems. In particular, these semi-structured NoSQL databases lead to a situation where some attributes (properties) are filled-in while other ones are not available, either because they exist but are missing (for instance the age of a person that is unknown) or because they are not applicable for a particular case (for instance the year of military service for a girl in countries where it is mandatory only for boys). Therefore, some keys can be provided for some nodes and not for other ones. In such a scenario, when we want to extract knowledge from these new generation database systems, we face the problem of missing data that arises need for analyzing them. Some approaches have been proposed to replace missing values so as to be able to apply data mining techniques. However, we argue that it is not relevant to consider such approaches because they may introduce biases or errors. In our work, we focus on the extraction of gradual patterns from property graphs that provide end-users with tools for mining correlations in the data when there exist missing values. Our approach requires first to define gradual patterns in the context of NoSQL property graph and then to extend existing algorithms so as to treat the missing values, because anti-monotonicity of the support can not be considered anymore in a simple manner. ...

The conference was launched and is supported by the European Federation for Information Technology in Agriculture, Food and the Environment (EFITA) with the collaboration of the World Congress on Computers in Agriculture (WCCA). ; International audience ; The agricultural ecosystem has already achieved its technical mechanical revolution, yet, like the whole society it faces with the "digital revolution" (computers, Internet, sensors, connected objects, etc…). This leads to a new phenomenon: the massive arrival of various data and, consequently, the importance of this data for information systems and beyond for decision support systems (usually in the form of a data warehouse exploitable by various exploration methods). In response to emerging issues such as sustainable development and adaptation to climate change, agricultural organizations and governments in charge of information delivery and decision-making systems must manage and implement new information systems to adapt to these new challenges.

The conference was launched and is supported by the European Federation for Information Technology in Agriculture, Food and the Environment (EFITA) with the collaboration of the World Congress on Computers in Agriculture (WCCA). ; International audience ; The agricultural ecosystem has already achieved its technical mechanical revolution, yet, like the whole society it faces with the "digital revolution" (computers, Internet, sensors, connected objects, etc…). This leads to a new phenomenon: the massive arrival of various data and, consequently, the importance of this data for information systems and beyond for decision support systems (usually in the form of a data warehouse exploitable by various exploration methods). In response to emerging issues such as sustainable development and adaptation to climate change, agricultural organizations and governments in charge of information delivery and decision-making systems must manage and implement new information systems to adapt to these new challenges.

The conference was launched and is supported by the European Federation for Information Technology in Agriculture, Food and the Environment (EFITA) with the collaboration of the World Congress on Computers in Agriculture (WCCA). ; International audience ; The agricultural ecosystem has already achieved its technical mechanical revolution, yet, like the whole society it faces with the "digital revolution" (computers, Internet, sensors, connected objects, etc…). This leads to a new phenomenon: the massive arrival of various data and, consequently, the importance of this data for information systems and beyond for decision support systems (usually in the form of a data warehouse exploitable by various exploration methods). In response to emerging issues such as sustainable development and adaptation to climate change, agricultural organizations and governments in charge of information delivery and decision-making systems must manage and implement new information systems to adapt to these new challenges.

The conference was launched and is supported by the European Federation for Information Technology in Agriculture, Food and the Environment (EFITA) with the collaboration of the World Congress on Computers in Agriculture (WCCA). ; International audience ; The agricultural ecosystem has already achieved its technical mechanical revolution, yet, like the whole society it faces with the "digital revolution" (computers, Internet, sensors, connected objects, etc…). This leads to a new phenomenon: the massive arrival of various data and, consequently, the importance of this data for information systems and beyond for decision support systems (usually in the form of a data warehouse exploitable by various exploration methods). In response to emerging issues such as sustainable development and adaptation to climate change, agricultural organizations and governments in charge of information delivery and decision-making systems must manage and implement new information systems to adapt to these new challenges.

The conference was launched and is supported by the European Federation for Information Technology in Agriculture, Food and the Environment (EFITA) with the collaboration of the World Congress on Computers in Agriculture (WCCA). ; International audience ; The agricultural ecosystem has already achieved its technical mechanical revolution, yet, like the whole society it faces with the "digital revolution" (computers, Internet, sensors, connected objects, etc…). This leads to a new phenomenon: the massive arrival of various data and, consequently, the importance of this data for information systems and beyond for decision support systems (usually in the form of a data warehouse exploitable by various exploration methods). In response to emerging issues such as sustainable development and adaptation to climate change, agricultural organizations and governments in charge of information delivery and decision-making systems must manage and implement new information systems to adapt to these new challenges.