Research themes
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Investigation of multi-dimensional datawarehouses able to store complex and heterogeneous data. Extension of query languages with data mining functionalities for a more relevant and access to relevant information.
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Investigation of automatic model and knowledge acquisition methods from massive data with a focus on temporal and spatial patterns. Data stream analysis and model updating in order take into account data novelty. Investigation of incremental learning methods.
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Development of decision-aiding tools to help a user analyze data at hand (simulation results, for instance) by extracting interesting patterns and recommending actions. Investigation of interactive learning methods tools.
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Investigation of the interaction between diagnosis and decision in uncertain universes and, particularly, recommending actions from simulation results.
For more details see the annual project activity report.
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