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themes [2016/10/11 11:18]
philippereneviergonin [FOrmalizing and Reasoning with Users and Models]
themes [2019/11/15 16:01] (current)
philippereneviergonin
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-The SPARKS team is composed by Themes.+The SPARKS team is composed by Themes.
  
 ===== Knowledge Extraction and Learning ===== ===== Knowledge Extraction and Learning =====
  
 +The activity in this research theme has mainly focused on the development of methods and algorithms
 +exploiting ideas and techniques from machine learning, data mining, natural language processing, and artificial
 +intelligence for extracting novel, useful information and knowledge from data. Many kinds of data have been
 +considered, ranging from structured data in tabular form (records with numerical and/or categorical attributes)
 +to unstructured data such as text in natural language, graphs (as diverse as social networks, see
 +also FORUM theme, gene regulatory networks, and linked data) and multimedia data, including time
 +series (e.g., electrocardiographic signals), images, videos and 3D data.
 +The methods and techniques used include support-vector machines, neural networks,
 +boosting, decision trees, random forests, frequent pattern and association rule mining , inductive logic programming,​ fuzzy set theory, and evolutionary algorithms.
  
 +A particular emphasis has been given to the scalability of the approaches, according to three dimensions:
 +   - the volume of the data that are to be processed;
 +   - the number of processing units available for computation and the distributed nature of both data and algorithms;
 +   - the computational power of the processing units, which may become critical when the proposed approaches must be embedded in appliances, vehicles, or mobile devices, often with tight resource consumption constraints.
  
  
  
-===== FOrmalizing and Reasoning with Users and Models =====+===== FOrmalizing and Reasoning with Users and Models ​(FORUM) ​=====
  
  
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 representation from the semantic Web to propose new analysis tools and indicators, and support new representation from the semantic Web to propose new analysis tools and indicators, and support new
 functionalities and better management. functionalities and better management.
-The research objectives of this theme can be grouped according to three main topics: (1) supporting ​HumanComputer+ 
 +The research objectives of this theme can be grouped according to three main topics: (1) supporting ​Human Computer
 Interaction (HCI) and Human Data Interaction (HDI), (2) supporting interaction between users Interaction (HCI) and Human Data Interaction (HDI), (2) supporting interaction between users
 and (3) reasoning and interacting with knowledge graphs. As a corollary, we design user-centered models and and (3) reasoning and interacting with knowledge graphs. As a corollary, we design user-centered models and
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 +With the generalisation of multi-cores and distributed computing resources, programmers face new software
 +parallelisation,​ adaptability,​ and scaling-up complexities. SPARKS research in that field is grounded on
 +a long-standing experience in the domains of scientific workflow systems that facilitate distributed computing
 +infrastructures exploitation by non-expert users, scalable and secure software composition techniques, and
 +adaptation to heterogeneous and dynamic execution environments. In addition, part of the activity ​
 + ​complements the research theme FORUM theme with concerns related to large-scale
 +distributed data repositories integration.
 +
 +
 +
 +===== Computer Science and Biology =====
  
 +Computer science finds in biology an inexhaustible source of new problems and a remarkable field of inspiration. On the one hand, 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. On the other hand, there are countless bio-inspired techniques that have made major research contributions,​ as neuroscience-inspired and genetics-inspired learning techniques.
  
 +SPARKS has a long standing experience in data management, model design, model simulation and formal reasoning for biology as well as in bio-inspired learning techniques.
  
 +More details about :
 +  * [[https://​msn.i3s.unice.fr/​|models and simulations for neurosciences]]  ​
 +  * [[https://​bioinfo.i3s.unice.fr/​en/​index.php|formal methods for biology]]
  • themes.1476177523.txt.gz
  • Last modified: 2016/10/11 11:18
  • by philippereneviergonin