Thesis supervisor: Balázs János Villányi
Location of studies (in Hungarian): Department of Electronics Technology Abbreviation of location of studies: ETT
Description of the research topic:
"Enterprise Information Systems (EIS) are more and more important in the corporate world, thus their reliable and efficient operation is a key issue. These systems incorporate a wide scale information techniques, their integration to provide unified services is a quintessential part of the efficient operation. Enterprise Application Integration (EAI) is the framework to support this endeavor and provides techniques to this end.
Also, there are other means to integrate enterprise systems. Schema Matching (SM) enables the establishment of semantic correspondence among the data of heterogeneous Enterprise Information Systems (EIS). There have been several viable schema matching propositions, but still their matching accuracy can be further improved.
This PhD research topic includes, but not limited to the following research tasks:
• Performance evaluation and improvement of EAI approaches
• Development of novel EAI techniques
• Investigate and improve existing SM algorithms
• Develop new SM techniques
• Apply Machine Learning (ML) to SM approaches
• Apply Fuzzy Logic to SM approaches
• Create research evaluation environment for EAI and SM solutions
The developed techniques should be implemented by potentially using the available industrial standards, open source solutions and shall be validated in several test scenarios."
Required language skills: English Number of students who can be accepted: 1
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