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Knowledge Discovery from Databases (KDD) is a nontrivial process of extraction of previously unknown and potentially useful information from data (Frawley et al 1992). An essential element of KDD is Data Mining (Elmasri and Navathe 2003, p.868 and Fayyad 1996), which is concerned with identifying patterns in and associations between data inductively. The core topics involved in data mining are classification, clustering and association rules (Dunham 2003 pp.73-191). KDD is thus far applied to only single databases, and no work is reported as far as we know on how KDD may be performed on semantically interoperable databases, i.e., autonomous databases that are capable of working together through mappings on the basis of semantics of data.
We, the Database and Semantic Web Research Group at UWS, have been successfully exploring semantic interoperability between ontologies (Feng and Wang 2009, Wang 2008, Wang and Feng 2007), between databases (Yang 2009), between an ontology and a database (Zhu and Feng 2008, 2010) and semantic web services (Manrti and Feng 2010a, 2010b) by drawing on Barwise and Seligman’s (1997) Information Flow Theory (known colloquially as channel theory) and Formal Concept Analysis (Wille 1997). We also explored how a ‘representational relationship’ between two sets of objects may be identified and formulated (Wang 2008), how such a relationship may be measured (Feng and Wang 2009), and how the fundamental notion of ‘information content of data’ in a database may be defined and how the information content of data may be reasoned about with a view to deducing otherwise hidden information (Feng and Salt 2010, Xu et al 2008, Wu and Feng 2009).
Building upon the above successfully completed work including PhD programmes and MSc projects, we envisage that this proposed project would involve:
Establishing semantic interoperability between databases;
Creating a model for an integrated semantically interoperable database system;
Developing notions, inference rules and mechanisms for reasoning about the information content of data at different levels for discovering hidden information and knowledge.
The ideal candidate should hold a 2.1 or above Honours degree in computer science, information systems, or a closely related discipline. A relevant master’s degree would be an advantage. Candidates with relevant research or industrial experience would be especially welcome.
Funding Notes:
Successful candidates will receive a £6000 annual stipend payable for three years and payment of tuition fees (current value £3400).
This studentship is open to Home/EU candidates with a first degree in a relevant discipline.
Non-EU students can apply, but will not receive the stipend and will be required to pay fees.
Candidates must be available to commence their studies in October 2012.
All interviews will take place during between 21st May and 8th June 2012.
Please note that this project is part of a competitive round and there is no guarantee that it will be awarded.
References:
How to apply:
Postgraduate Degree by Research Applications should be completed online at http://www.uws.ac.uk/research/research-degrees/apply/
Please quote the Project Reference Number when applying.
Applications without all relevant documents will not be considered.
If you have any queries please contact Charlie Fielding on + 44 (0)141 848 3919 or email PGR@uws.ac.uk