Research on reconciliation and integration of complex networks created by Big Data Analytics and semantic modelling

    • Definition of an ontology, explaining and linking different kinds of goal oriented data that are able to describe the business goals for data extraction in the context of Big Data Analytics, Complex Networks, and application for e-Health.
    • The ontology that will be developed should be apt to data transformation and model creation based on the results of Big Data Analytics and Complex Networks.
    • The representation of ontology should be fitted to the requirements of Big Data Analytics
    • The cognitive technologies and cognitive computing can be exploited on the basis of ontologies. Stepping beyond the readily available Big Data Analytics and Computational Intelligence Techniques, the semantic interpretation of data demands technologies that makes the data, complex networks, models represented by ontologies human readable.
    • Investigation the possible solutions:
    1. To ingest large volumes of heterogeneous electronic data using Big Data technologies;
    2. To analyse data for individual entities (e.g. patients) by comparing them to their peers using pluggable predictive analytics components that assess various forms of data combination;
    3. How can be unstructured and structured databases integrated through supporting ontologies. A scalable and general approach for predictive analytics and reporting should be created that satisfies several key requirements:
    4. Universal Standards-Based Analytics Environment; Open Data Access; Analytics Design; Scalable for Large and Dynamic Data Sets, Unstructured and structured data repository and ingest of ontologically defined data.
    • Available techniques, methods, tools and technologies:
      • Description Logic, and its languages (OWL, OWL2);
      • Representation of Ontologies;
      • Big Data Analytics, Computational Intelligence, Machine Learning;
      • Data Mining and Database Management Technologies

    Thesis supervisor: Bálint Molnár

    How to Apply?

    If you are interested apply here: [PhD] Doctoral School of Informatics – Eötvös Loránd University (elte.hu)

    For more information visite the folllowing website: Doctoral School of Informatics (elte.hu)

  • Funded: Not Funded

    Master Degree: Required

    Duration: 4 Years

    Starting Date: 06 September 2021

    Deadline to Apply: 31 May 2021

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