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--- themes [2016/10/11 11:14]
philippereneviergonin created
+++ themes [2016/10/11 11:23]
philippereneviergonin [Knowledge Extraction and Learning]
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+====== Themes ======
+The SPARKS team is composed by 3 Themes.
+===== 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 (FORUM) =====
+Activities within this research theme address the general problem of reconciling formal semantics of computer
+science (e.g. logics, ontologies, typing systems, protocols, etc.) on which the Web architecture is built, with
+soft semantics of people (e.g. posts, tags, status, relationships, etc.) on which the Web content is built. The
+research works in this theme contribute to the understanding of these graphs by (1) proposing multidisciplinary
+approaches to analyze and model the many aspects of these intertwined information systems, their communities
+of users and their interactions, and (2) formalizing and reasoning on these models using graph-based knowledge
+representation from the semantic Web to propose new analysis tools and indicators, and support new
+functionalities and better management.
+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
+and (3) reasoning and interacting with knowledge graphs. As a corollary, we design user-centered models and
+methods and we conduct user experimentations and user evaluations of the algorithms and platforms we develop.
+===== Scalable Software Systems =====
+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.