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Thesis topic proposal
 
Bálint Molnár
Research on reconciliation and integration of complex networks created by Big Data Analytics and semantic modelling

THESIS TOPIC PROPOSAL

Institute: Eötvös Loránd University, Budapest
computer sciences
Doctoral School of Informatics

Thesis supervisor: Bálint Molnár
Location of studies (in Hungarian): ELTE Faculty of Informatics
Abbreviation of location of studies: ELTE


Description of the research topic:

● 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:
i) To ingest large volumes of heterogeneous electronic data using Big Data technologies;
ii) 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; and
iii) 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:
iv) 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:
o Description Logic, and its languages (OWL, OWL2);
o Representation of Ontologies;
o Big Data Analytics, Computational Intelligence, Machine Learning;
o Data Mining and Database Management Technologies

Required language skills: English
Recommended language skills (in Hungarian): German
Number of students who can be accepted: 2

Deadline for application: 2018-05-31


2024. IV. 17.
ODT ülés
Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).

 
All rights reserved © 2007, Hungarian Doctoral Council. Doctoral Council registration number at commissioner for data protection: 02003/0001. Program version: 2.2358 ( 2017. X. 31. )