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Developing efficient algorithms for clustering and/or classification of large and complex data (DELAIGLESIAU16SF)

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  • Full or part time
    Dr de la Iglesia
  • Application Deadline
    No more applications being accepted
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

Dr. de la Iglesia’s main research interests are in developing data mining algorithms and in their application to areas such as medical data and financial data. Past projects have included Privacy Preserving Data Mining, clustering and classification using optimisation techniques, creation, simplification and presentation of rule sets, text mining and preparation and analysis of health data. Current projects include extraction of data from multiple Hospital Information Systems to create clinical pathways and the analysis of complex data using clustering algorithms. She would welcome applications from students who have secured their own funding and who wish to work in any areas of data mining algorithm development in line with her previous research or on applications of data mining that are not standard and present some research challenges. Dr. de la Iglesia is willing to discuss specific PhD project proposals that fall within that remit and may have some readily available projects in the analysis of previously collected health data.

Funding Notes

This PhD project is offered on a self-funding basis. It is open to applicants with funding or those applying to funding sources. Details of tuition fees can be found at http://www.uea.ac.uk/pgresearch/pgrfees.

A bench fee is also payable on top of the tuition fee to cover specialist equipment or laboratory costs required for the research. The amount charged annually will vary considerably depending on the nature of the project and applicants should contact the primary supervisor for further information about the fee associated with the project.

References

Hills, J, Bagnall, A, De La Iglesia, B and Richards, G (2013) BruteSuppression: a size reduction method for Apriori rule sets. Journal of Intelligent Information Systems. ISSN 0925-9902
De La Iglesia, B, Ong, ACL, Potter, JF, Metcalf, AK and Myint, PK (2012) Predictors of orthostatic hypotension in patients attending a transient ischaemic attack clinic: Database study. Blood pressure, Epub ahead of print. pp. 1-8. ISSN 1651-1999
Reynolds, A and de la Iglesia, B (2009) A multi-objective GRASP for partial classification. Soft Computing - A Fusion of Foundations, Methodologies and Applications, 13 (3). pp. 227-243.

Alotaibi, Khaled and De La Iglesia, Beatriz (2013) Privacy-Preserving SVM Classification using Non-metric MDS. In: SECURWARE 2013, the Seventh International Conference on Emerging Security Information, Systems and Technologies. IARIA, pp. 30-35.

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