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--- start [2016/07/22 07:18] – philippereneviergonin
+++ start [2022/02/28 10:15] (current) – jaillet
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-====== Equipe SPARKS  ======
+====== SPARKS TEAM  ======
+SPARKS is an acronym for **S**calable and **P**ervasive softw**AR**e and **K**nowledge **S**ystems
-L'équipe SPARKS (Scalable and Pervasive softwARe and Knowledge Systems) est une structure de recherche interne au laboratoire [[http://www.i3S.unice.fr|Informatique, Signal et Systèmes de Sophia Antipolis]] (I3S), UMR 7271 entre le [[http://www.cnrs.fr|CNRS]] et l'[[http://www.unice.fr|Université Nice Sophia Antipolis]]. Le nom précédent de l'équipe SPARKS était l'équipe (ou pôle) GLC.
+**Head** : Marco Winckler deputised by Jean-Paul Comet.
+The team investigates the organization, the representation, and the distributed processing of knowledge, as well as its extraction from data and its semantic formalization. A particular attention is dedicated, on the one hand, to large-scale architectures and massive data and, on the other hand, to the design of human- and knowledge-centered, evolutionary and adaptive software systems.
+The team’s scientific objectives are therefore naturally structured around four main research themes:
+   * **knowledge extraction and learning** : focusing on the development and application of data mining, machine learning, knowledge discovery methods, the automatic construction of ontologies and automatic knowledge-base enrichment;
+   * **formalizing and reasoning with users and models** : studying the different types of knowledge-based interactions, like interactions with and between users and reasoning with knowledge graphs; topics thus include (graph-based) knowledge representation, reasoning, cognitive agents, information integration and fusion, user modeling, ambient intelligence, on-line communities and social networks;
+   * **scalable software systems** : focusing on models of distributed computation, scalability, dynamic adaptation and composition of evolutionary software systems.
+   * **Computer Science and Biology** : computer science is necessary for pushing forwards the knowledge frontiers in biology using, e.g., ontologies, data mining, knowledge extraction, modelling and simulation of dynamic biological systems, formal proofs about the behaviour of biological systems and more generally model-based reasoning assisted by computers. There are also countless bio-inspired techniques that have made major research contributions, as neuroscience-inspired and genetics-inspired learning techniques.
-L'équipe SPARKS recouvre en particulier les aspects liés à :
+The keywords that best describe the areas of interest of the team’s members and their field of activity are the following (sorted by order of importance):
+   * Software Engineering;
+   * Knowledge Representation and Management
+   * Semantic Web;
+   * Human-Computer Interaction;
+   * Artificial Intelligence;
+   * Ambient Intelligence;
+   * Data Mining;
+   * Reasoning;
+   * Natural Language Processing;
+   * Big Data;
+   * Machine Learning.
+   * Information Systems;
+   * Computer-Based Environments for Human Learning;
+   * Algorithms;
+   * Large-Scale Infrastructures;
+   * Multi-Agent Systems;
+   * Distributed Systems.
-    * la maîtrise de la complexité logicielle,
-    * la dynamicité et l’adaptabilité, en particulier en fonction de l’évolution du contexte d’exécution,
-    * la globalisation des calculs et leur déploiement sur des infrastructures distribuées,
-    * la description sémantique des processus et des données,
-    * la construction et l’utilisation des bases de connaissances.
-{{ :public:seminars_manifestations:poleday2012b-helene-04.jpg?400 |}}
+The SPARKS tream includes a "common project-team" between I3S and INRIA : [[http://wimmics.inria.fr/|wimmics: web-instrumented man-machine interactions, communities and semantics]]
-Responsables :
+/* [[:presentation|More information...]]
+*/
-    * Responsable de l'équipe : Andrea G. B. Tettamanzi <Andrea.Tettamanzi@unice.fr>
+ {{ :public:seminars_manifestations:poleday2012b-helene-04.jpg?400 |}}
-    * Suppléant: Johan Montagnat <johan@i3s.unice.fr>
-Il est constitué de trois thèmes :
-    * Knowledge Extraction and Learning : développer des méthodes et algorithmes basés sur l'apprentissage automatique (//machine learning//), la fouille de données (//data mining//), l'intelligence artificielle (//artificial intelligence//) pour extraire des données de nouvelles et utiles informations et connaissances.
-    * FOrmalizing and Reasoning with Users and Models : comprendre les données (1) en proposant des approches pluridisciplinaires d'analyse et de modélisation multi-critères des systèmes d'information, des communautrés d'utilisateurs et de leurs interactions et (2) en raisonnant sur ces modèles en utilisant les approches orientées graphes du //Semantic Web// pour proposer de nouveaux outils d'analyse et pour créer de nouvelles fonctionnalités et une meilleure gestion.
-    * Scalable Software Systems : adapter et composer les systèmes, les données et les flux de travaux (//workflow//) à différentes échelles, de la boucle locale à la distribution massive.
-[[:presentation|Pour en savoir plus...]]
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