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Financement de l’UE (10 M €) : Des analyses axées sur l’expérience utilisateur et l’expérience utilisateur pour des résultats et des décisions extrêmement précis Hor 25/11/2022 Programme de recherche et d'innovation de l'UE « Horizon »
Vue d’ensemble
Texte
Des analyses axées sur l’expérience utilisateur et l’expérience utilisateur pour des résultats et des décisions extrêmement précis
Extreme data characteristics (volume, speed, heterogeneity, distribution, diverse quality, etc.) challenge the state-of-the-art data-driven analytics and decision-making approaches in many critical domains such as crisis management, predictive maintenance, mobility, public safety, and cyber-security. At the same time, data-driven insights need to be extremely timely, accurate, precise, fit-for-purpose, and trustworthy, so that they can be useful. ExtremeXP will handle the complexity of matching extreme needs with complex analytics processes (i.e., processes that involve and combine ML, data analysis, simulation and visualization components) by placing the end user at the centre of complex analytics processes and relying on user intents and running experiments (i.e., trial and error) to prune the vast solution space of possible analytics workflows and configurations i.e., “variants”. Its main goal is to create a next generation decision support system that integrates novel research results from the domains of data integration, machine learning, visual analytics, explainable AI, decentralised trust, knowledge engineering, and model-driven engineering into a common framework. The overarching idea of the framework is to optimise the properties of a complex analytics process that the end user cares about (e.g., accuracy, time-to-answer, specificity, recall, precision, resource consumption) by associating user profiles to computation variants. The framework is envisioned as modular and extensible, orchestrating different services around an Experimentation Engine: Analysis-aware Data Integration, Extreme Data & Knowledge Management, User-driven AutoML, Transparent & Interactive Decision Making, and User-driven Optimization of Complex Analytics. The framework will be validated in five pilot demonstrators.
| Bournemouth University | ? |
| Activeeon | 573 750 € |
| Airbus DS SLC | 562 538 € |
| Athina-Erevnitiko Kentro Kainotomias Stis Technologies TIS Pliroforias, TON Epikoinonion Kai TIS Gnosis | 814 672 € |
| Bitsparkles | 420 000 € |
| CS Group - France | 589 375 € |
| Deutsches Forschungszentrum FUR Kunstliche Intelligenz GmbH | 431 375 € |
| Erevnitiko Panepistimiako Institouto Systimaton Epikoinonion Kai Ypologiston | 536 875 € |
| Fundacio Privada I2Cat, Internet i Innovacio Digital A Catalunya | 525 400 € |
| Ideko S Coop | 362 500 € |
| Interactive 4D | 473 750 € |
| Intracom Single Member SA Telecom Solutions | 662 500 € |
| Ithinkupc SL | 0,00 € |
| Moby X Software Ltd. | 412 500 € |
| Sintef AS | 621 033 € |
| Stichting Amsterdam UMC | 0,00 € |
| Stichting VU | 669 978 € |
| Technische Universiteit Delft | 831 076 € |
| Universitat Politecnica de Catalunya | 746 875 € |
| Univerza V Ljubljani | 354 625 € |
| Univerzita Karlova | 423 000 € |
https://cordis.europa.eu/project/id/101093164
Cette annonce se réfère à une date antérieure et ne reflète pas nécessairement l’état actuel. L’état actuel est présenté à la page suivante : Bournemouth University EDUCATIONAL CORPORATION, Poole, Royaume Uni.
