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Massive Data Management, Analysis and Exploration - MADAX

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The main goal of the MADAX project is to devise, study, implement and experimentally validate techniques for efficient management and analysis of massives semi-structured data sets, with a particular focus on Web and graph data. Interests of the project include static analysis, data summary inference, workflow management and analysis, provenance and data integration, with a particular interest on approaches relying on systems and paradigms for shared-nothing parallelism (MapReduce, Spark, Giraph).

Members of the project collaborate with members of the machine learning project on problems related to large scale recommandations systems.