A semantic web model for ad hoc context-aware communities : Application to the Smart Place Scenario

International audienceIn this paper, we propose a model for an open framework that allows mobile users to create and to participate to context-aware virtual communities. The model we propose and implement is a generic data model fully compliant with the semantic web data model RDF. This model is suited to let mobile end-users use, create and customize virtual communities. We combine fundamentals for a decentralized semantic web social network with context-aware virtual communities and services. Smart cities scenarios are typically targeted with this approach. It can be implemented in places like metro stations, museums, squares, cinemas, etc. to provide ad hoc context-aware information services to mobile users

Behaviour-based identification of student communities in virtual worlds

VirtualWorlds (VW) have gained popularity in the last years in domains like training or education mainly due to their highly immersive and interactive 3D characteristics. In these platforms, the user (represented by an avatar) can move and interact in an artificial world with a high degree of freedom. They can talk, chat, build and design objects, program and compile their own developed programs, or move (flying, teleporting, walking or running) to different parts of the world. Although these environments provide an interesting working place for students and educators, VW platforms (such as OpenCobalt or OpenSim amongst others) rarely provide mechanisms to facilitate the automatic (or semi-automatic) behaviour analysis of users interactions. Using a VW platform called VirtUAM, the information extracted from different experiments are used to analyse and define students communities based on their behaviour. To define the individual student behaviour, different characteristics are extracted from the system, such as the avatar position (in form of GPS coordinates) and the set of actions (interactions) performed by students within the VW. Later this information is used to automatically detect behavioural patterns. This paper shows how this information can be used to group students in different communities based on their behaviour. Experimental results show how community identification can be successfully perform using K-Means algorithm and Normalized Compression Distance. Resulting communities contains users working in near places or with similar behaviours inside the virtual world.This work has been funded by the Spanish Ministry of Science and Innovation under the project ABANT (TIN2010-19872/TSI)

Intelligent web applications as future generation of web applications

During the recent years World Wide Web very fast increased a fundamental part in our everyday life. In commerce, personal relationship, the effect of the universal network has wholly changed the way people interact with each other and with machines. The problem is after rising the Artificial Intelligence to presenting human feelings, everything changed including web applications. In this paper, we describe the intelligent web applications as present and future of web applications, moreover we highlight the special features and their roles in increasing intelligence of web applications as well as impact this application in the process development web systems. The goals of this paper led to developers to create smart and modern web applications

Approches organisationnelles pour la conception de systèmes multi-agents dédiés à la gestion des connaissances; Application aux projets d'ingénierie et d'innovation Composition du jury

Approches organisationnelles pour la conception de systèmes multi-agents dédiés à la gestion des connaissances; Application aux projets d’ingénierie et d’innovatio

Assessing knowledge management systems implementation in Ghanaian universities

Knowledge management (KM) is regarded as a strategic asset and a source of competitive advantage for organisations. While the issues of KM have been widely discussed by many researchers, there is a paucity of studies pertaining to the role of KM in enhancing the performance of universities, especially Ghanaian universities. Similarly, there is the lack of formal strategy that would provide an appropriate framework for these systems to ensure maximum utilisation of available knowledge for competitive advantage. Due to this, Ghanaian universities have been continually reinventing the wheel each time they lose knowledge through expertise leaving the universities. This loss of knowledge through expert staff exiting raises the need to have systems and strategies in place that will help the universities to capture that relevant knowledge. The research thus set out to address these problems by assessing the implementation of KM systems in Ghanaian universities and the strategies that could be adopted to manage and safeguard knowledge as a competitive advantage and for future use. A survey and a mixed method research approach, which encompasses a questionnaire and interview schedules, were used to collect data from the stratified sampled respondents. One hundred and eighteen (80.27%) questionnaires were successfully received from the respondents, while all nine interviewees successfully responded to the interviews. Pattern matching, content analysis and explanation-building were used to analyse the qualitative data. The Microsoft spreadsheet and SPSS software were used to analyse the quantitative data and descriptive statistics in the form of tables, pie charts and histograms were used to present the findings. The findings of this study showed that: the concepts of KM was universally understood by the respondents; KM processes were effective; systems and facilities such as internet, intranet, e-mails, mobile technology and DVD/VCD/CD were used to facilitate KM at the universities; leadership, culture, technologies and strategies were the KM enablers; e-learning, coaching and mentorship, communities of practice, and storytelling were the main strategies used to manage and safeguard knowledge; and KM systems had a positive impact on the universities. The study finally formulated an integrated KM framework to guide the implementation of KM systems in universities.Information ScienceD. Litt. et Phil. (Information Science

Détection de communautés dynamiques dans des réseaux temporels

La détection de communauté dans les réseaux est aujourd'hui un domaine ayant donné lieu à une abondante littérature. Depuis les travaux de Girvan et Newman en 2002, des centaines de travaux ont été menés sur le sujet, notamment la proposition d'un nombre important d'algorithmes de plus en plus élaborés. Si, au départ, le découpage était un partitionnement -chaque nœud appartenait à une et une seule communauté, unique et statique- les méthodes ultérieures ont montré l'intérêt de communautés imbriquées, ou décomposées hiérarchiquement. Encore plus récemment, certains travaux ont commencé à s'intéresser aux communautés dans des réseaux temporels, c'est à dire à des communautés qui évoluent au cours du temps, selon les modifications du réseau. C'est à ce nouveau problème que j'ai consacré cette thèse. Mon état de l'art, après avoir présenté les méthodes statiques les plus connues, est consacré à l'étude des quelques méthodes déjà proposées pour la détection de communautés dynamiques - dont beaucoup ont été publiées au cours des années durant lesquelles j'ai fait ma thèse- ainsi qu'à leurs forces et faiblesses. Dans une seconde partie, je propose un framework (iLCD) permettant de détecter des communautés persistantes dans des réseaux évoluant fortement, représentés sous la forme de graphes d'intervalles (chaque lien existe pour une ou plusieurs périodes données). Ce framework est conçu pour traiter de grands graphes, éventuellement en temps réel. Je propose ensuite deux implémentations de ce framework, la première étant limitée à des réseaux sans disparition de liens (de type réseaux de citation). La dernière partie de ce chapitre est consacrée aux aspects pratiques de la détection de communautés dynamiques, en particulier comment manipuler les données en entrée (réseaux temporels) et en sortie (communautés dynamique), qui sont plus complexes que dans le cas statique. Deux outils de visualisation de communautés dynamiques sont proposés, leur nécessité étant apparue au cours ma thèse. Le problème de tout algorithme de détection de communautés est de prouver la pertinence des résultats qu'il trouve. J'ai donc consacré la troisième partie de la thèse à ce problème. Cela m'a conduit à m'interroger sur la définition de ce qu'est une bonne communauté, et j'ai en particulier distingué ce que j'ai appelé les communautés intrinsèques des communautés définies relativement au réseau. Afin de valider la pertinence des résultats trouvés, j'ai ensuite essayé de comparer les communautés données par ma méthode avec celles données par les algorithmes statiques les plus connus. Étant particulièrement intéressé par l'application à des graphes réels, et la comparaison aux autre algorithmes se faisant généralement sur des graphes générés, j'ai ensuite proposé deux approches originales pour comparer des communautés sur des graphes réels : l'une, basée sur l'expérimentation, demande à des utilisateurs de Facebook de comparer les communautés trouvées dans leur réseau personnel par différentes solutions. L'autre propose, via deux métriques complémentaires, de comparer les solutions fournies par des algorithmes différents sur un même réseau. Enfin, dans la dernière partie, je présente deux applications de cet algorithme à des réseaux réels dynamiques. Le but de ces applications est double : d'une part, montrer l'intérêt pratique de l'approche dynamique, et, d'autre part, valider l'applicabilité de l'algorithme proposé sur des réseaux réels. Le premier réseau, de petite taille, concerne l'évolution des groupes au sein d'une population animale ayant un comportement social, étudiée sur une période de plus de quinze ans. Ce travail a été fait en concertation avec des éthologues, ayant déjà travaillé sur ces données de manière statique. La deuxième application est menée sur un réseau de beaucoup plus grande taille, concernant le réseau complet d'une plateforme de partage de vidéo japonaise de type Youtube, appelée Nico Nico Douga. Dans les deux cas, une analyse détaillée des résultats obtenus est fournie, qui permet de se rendre compte de l'intérêt de mon approche.The detection of community in networks is a domain today having given rise in plentiful one literature. Since the works of Girvan and Newman in 2002, hundreds of works were led on the subject, in particular the proposal of a significant number of more and more developed algorithms. If, at first, the cutting(division) was a partitionnement - every knot belonged in one and a single community, unique(only) and static the later methods showed the interest of imbricated communities, or decomposed hierarchically. Even more recently, certain works began to be interested in communities in temporal networks, that is in communities which evolve in time, according to the modifications of the network. It is to this new problem that I dedicated this Thesis. My state of the art, having presented the most known static methods, is dedicated to the study of some methods already proposed for the detection of dynamic communities - among which many were published during the years in the course of which I made my thesis(theory) as well as for their strengths and weaknesses

Web Intelligence and Communities

ABSTRACT The World Wide Web (WWW) provides precious means for communication, which goes far beyond the traditional communication media. Web-based communities have become imperative spaces for individuals to seek and share expertise. Networks in these communities usually differ in their topology from other networks such as the World Wide Web. In this paper, we explore some research issues of web intelligence and communities. We will also introduce the WI&C'15 workshop's goal and structure

Web Intelligence and Communities

International audienc

Web Intelligence and Communities (Workshop introduction)

International audienceCommunities appear as a first-class object in the areas of web intelligence and agent technologies, as well as a crucial crossroads of several subdomains. These subdomains impact the nature of the communities and the applications that are related to them. These applications are numerous, and the success of well-known social network sites for entertainment should not be allowed to overshadow the other application domains, for instance, in education, health, design, knowledge management, and so forth

Research topics on Web Intelligence and Communities

International audienceWeb Intelligence deals with intelligent methods and information \& communication technologies that are integrated to enhance different web-based applications. Communities are popular, particularly on the World Wide Web, as a means for like-minded individuals to pursue common goals. Communities appear as a first-class object in the areas of web intelligence and agent technologies, as well as a crucial crossroads of several sub-domains (i.e. user modeling, protocols, data management, data mining, content modeling, etc.). These sub-domains impact the nature of the communities and the applications which are related to them. The use of Web Intelligence and communities is discussed together with ways in which a wide range of research is benefiting this area for the long-term