Objective
This coordination action will bring together newly emerging research in ubiquitous knowledge discovery.
Research areas are:
- data mining in mobile systems, wireless communication networks, calm technologies
- distributed architectures: distributed data mining, grid, P2P, autonomic computing,
- agents
- learning components: statistical learning (incl. online learning), evolutionary computing,
- anytime algorithms data types: spatio-temporal, stream, multimedia
- security and privacy: privacy preserving data mining, intrusion detection
- HCI and cognitive modelling: user interfaces of ubiquitous discovery systems
This multi-disciplinary approach constitutes a paradigm shift for the field of knowledge discovery since the idea of a standalone (desktop or workstation) analysis tool is abandoned in favour of process integrated, distributed and autonomous analysis systems. Work done in this area merely scratches the surface, is dispersed among several communities, and in a very early stage. Integration of the various sub-areas involves considerable risk. The CA KDubiq will act to close the gap and strengthen long-term research and applications in a new and future-oriented discipline ubiquitous knowledge discovery. It faces many new challenges, e.g. because of technical limitations in memory, CPU power, bandwidth etc, and can only succeed if privacy and security are addressed in a principled and multi-disciplinary manner.
Objectives are to identify new research challenges, emerging from the changing nature of information and information sources: achieving the vision of ubiquitous knowledge discovery as a transparent set of tools, to be exploited everywhere, anytime, by all to derive strategic guidelines for long-term research by blueprint editing to structure and support emerging multi-disciplinary communities to identify and foster new emergent technologies to be transferred to industry to provide an information service for, students, scientists, industry.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcomputer hardwarecomputer processors
- natural sciencescomputer and information sciencesdata sciencedata mining
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Topic(s)
Call for proposal
Data not availableFunding Scheme
CA - Coordination actionCoordinator
80686 MUENCHEN
Germany