Modèle d'influence pour le pilotage d'une décision de groupe

National audienceLa résolution collective d'un problème par un groupe d'agents est jalonnée de décisions sur lesquelles les agents doivent s'accorder. Les agents doivent coopérer pour déterminer efficacement quelle alternative retenir. Le débat correspondant est vu ici comme un processus dynamique que l'on cherche à analyser et contrôler. Sa dynamique dépend de la stratégie d'argumentation des agents, mais aussi de l'ordre dans lequel ceux-ci inter-viennent dans la délibération. Le jeu des acteurs, leur capacité à manœuvrer, à produire des coalitions sont alors autant de facteurs déterminants du processus dynamique de décision collective. Ce papier propose donc d'utiliser l'influence qu'un agent peut avoir dans un réseau social pour contrôler la dynamique du débat. Dans ce papier, le contrôle consiste simplement à dé-terminer l'agent le plus influent en temps réel et à lui donner la parole. La notion d'influence sociale est rattachée à la notion statistique de pouvoir décisionnel d'un individu dans un réseau social. Le pouvoir décisionnel est considéré ici comme une variable dynamique parce que variant dans le temps avec les préférences des agents : la probabilité qu'un agent ait une inclination pour une option est calculée à partir de l'utilité accordée à cette option chaque fois qu'un nouvel argument vient alimenter le débat, le pouvoir décisionnel est alors réactualisé. Enfin, celui-ci est utilisé comme un signal de commande pour contrôler la dynamique du débat

A text-mining and possibility theory based model using public reports to highlight the sustainable development strategy of a city

International audience—Nowadays, ecology and sustainable development are priority government's actions. In Europe, and more specifically in France, sustainable development (SD) is generally broken down into several distinct evaluation criteria. Each criterion is a requirement imposed by the government and corresponds to strategic stakes. When SD improvement actions are financed in an economic region or a city of the French territory by the government, a set of measures is usually set up to assess and control the impact of these actions. More precisely, these measures are used to check whether the region or the city has efficiently invested its budget in respect to the SD strategy of the government. This assessment process is a complex task for the government. Indeed, evaluations are only based on reports provided by the financed regions. These very numerous reports are written in natural language and thus, it is a thorny and time-consuming task for the government to efficiently identify the meaningful information in a plethora of reports and then objectively assess all the expected priorities. This project aims at automating the assessment process from the huge corpus of documents. Text-mining and segmentation techniques are introduced to automatically quantify the attention the region or the city pays to a given criterion. Obviously, this quantification can only be imprecisely determined. Then, the possibility theory is used to merge the information related to each criterion prioritization from all the documents. Finally, an application on the 265 largest cities in France shows the potential of the approach

User Centered and Ontology Based InformationRetrieval System for Life Sciences

Because of the increasing number of electronic data, designing efficient tools to retrieve and exploit documents is a major challenge. Current search engines suffer from two main drawbacks: there is limited interaction with the list of retrieved documents and no explanation for their adequacy to the query. Users may thus be confused by the selection and have no idea how to adapt their query so that the results match their expectations. 
This talk describes a request method and an environment based on aggregating models to assess the relevance of documents annotated by concepts of ontology. The selection of documents is then displayed in a semantic map to provide graphical indications that make explicit to what extent they match the user’s query; this man/machine interface favors a more interactive exploration of data corpus.
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From Theoretical Framework To Generic Semantic Measures Library

International audienceThanks to the ever-increasing use of the Semantic Web, a growing number of entities (e.g. documents) are characterized by non-ambiguous mean-ings. Based on this characterization, entities can subsequently be compared us-ing semantic measures. A plethora of measures have been designed given their critical importance in numerous treatments relying on ontologies. However, the improvement and use of semantic measures are currently hampered by the lack of a dedicated theoretical framework and an extensive generic software solution dedicated to them. To meet these needs, this paper presents a unified theoretical framework of graph-based semantic measures, from which we developed the open source Semantic Measures Library and toolkit; a solution that paves the way for straightforward design, computation and analysis of semantic measures for both users and developers. Downloads, documentation and technical support at dedicated website http://www.semantic-measures-library.org

USI: a fast and accurate approach for conceptual document annotation

International audienceBackground : Semantic approaches such as concept-based information retrieval rely on a corpus in which resources are indexed by concepts belonging to a domain ontology. In order to keep such applications up-to-date, new entities need to be frequently annotated to enrich the corpus. However, this task is time-consuming and requires a high-level of expertise in both the domain and the related ontology. Different strategies have thus been proposed to ease this indexing process, each one taking advantage from the features of the document.Results : In this paper we present USI (User-oriented Semantic Indexer), a fast and intuitive method for indexing tasks. We introduce a solution to suggest a conceptual annotation for new entities based on related already indexed documents. Our results, compared to those obtained by previous authors using the MeSH thesaurus and a dataset of biomedical papers, show that the method surpasses text-specific methods in terms of both quality and speed. Evaluations are done via usual metrics and semantic similarity.Conclusions : By only relying on neighbor documents, the User-oriented Semantic Indexer does not need a representative learning set. Yet, it provides better results than the other approaches by giving a consistent annotation scored with a global criterion instead of one score per concept

OBIRS-feedback, une méthode de reformulation utilisant une ontologie de domaine

National audienceLes performances d'un système de recherche d'information (SRI) peuvent être dégradées en termes de précision du fait de la difficulté pour des utilisateurs à formuler précisément leurs besoins en information. La reformulation ou l'expansion de requêtes constitue une des réponses à ce problème dans le cadre des SRI. Dans cet article, nous proposons une nouvelle méthode de reformulation de requêtes conceptuelles qui, à partir de documents jugés pertinents par l'utilisateur et d'une ontologie de domaine, cherche un ensemble de concepts maximisant les performances du SRI. Celles-ci sont évaluées, de manière originale, à l'aide d'indicateurs dont une formalisation est proposée. Cette méthode a été évaluée en utilisant notre moteur OBIRS, l'ontologie de domaine MeSH et la collection de tests MuCHMORE

How to handle the Decision-Maker's awareness of industrial context in his objectives declaration?

International audienceThis study investigates some new approaches that concern the handling of human considerations in the decision-aiding field. We particularly look for the industrial context change and the awareness of the Decision-Maker with regards to such a change, in his decisions. Beyond the Routine regular situation, three situations are thus considered, namely the Control, the Emergency Crisis and the Loss of Control. A proposition of definition and use of the Decision-Maker awareness is applied to the case of re-declaring initial objectives. Awareness is defined through three parameters which are the Belief, the Level and the Graduality, which make up to the so-called Awareness Unit Cube. This is assumed to be evolving with regards to the Decision-Maker perception evolution. According to the evolving values of these parameters on the one hand, and to the characterisation of the occurred situation on the other hand, mathematical adjustments of the considered objectives values are proposed. Some illustrations of the proposal are extracted from a case study submitted by a steel manufacturer

Formalisation possibiliste du dilemme volonté /capacité à faire

International audienceIf there is an awareness of the coexistence of the two stakes Will or desire to do and Capacity to do, few works address the problem of performance satisfaction in a multi-criteria space while integrating into the decision model feasibility considerations. Hereafter, we propose methods that can help the decision makers to find a compromise between willingness to do and ability to do in the uncertainty context, for instance, of the preliminary design stage. For this purpose, possibilistic models of the expected performance and also of the ability are defined. The difficulty of realization is calculated in a same way as the estimation of the satisfaction of performance using Choquet integral. Thus it may be possible to satisfy the customers while considering the available engineering resources.S'il y a bien une prise de conscience de la coexistence des deux référentiels Volonté de faire et Capacité à faire, peu de travaux s'intéressent à la satisfaction des performances dans un espace multicritère tout en intégrant dans le modèle de décision des estimations de faisabilité. Aussi proposons nous des méthodes outillées pour aider le décideur à réaliser un compromis entre volonté à faire et capacité à faire dans un contexte d'incertitude tel que celui de la conception préliminaire. A cet effet, des modèles possibilistes des performances attendues et aussi de la capacité à les atteindre sont définis. A l'instar de l'estimation de la satisfaction des performances agrégées de plusieurs critères, la difficulté de réalisation de celles-ci est aussi calculée par une l'intégrale de Choquet. Ainsi il doit être possible de satisfaire au mieux les clients en cohérence avec les ressources d'ingénierie mobilisables

Automatic Detection and Classification of Argument Components using Multi-task Deep Neural Network

International audienceIn this article we propose a novel method for automatically extracting and classifying argument components from raw texts. We introduce a multi-task deep learning framework exploiting weight parameters trained on auxiliary simple tasks, such as Part-Of-Speech tagging or chunking, in order to solve more complex tasks that require a fine-grained understanding of natural language. Interestingly, our results show that the use of advanced deep learning techniques framed in a multi-task setting enables competing with state-of-the-art systems that depend on handcrafted features