Postgraduate supervision

Current research topics in data mining

Academic background for students

Students who wish to be considered for the Msc and PhD research topics must first of all satisfy the EBIT faculty requirements available in the year book. Students who wish to be considered for the Msc research topics must have a Bsc honours degree in Computer Science and should have studied and passed Mathematics or Statistics at the undergraduate level up to the third year. Students who wish to be considered for the PhD research topics must additionally have a masters degree in Computer Science and a strong background in artificial intelligence methods or statistical modeling or both. Students are also expected to have successfully completed a course in research methods, or be prepared to register for a course in research methods.


Msc topics

Two topics are available on the comparison of binary classification methods for modeling from large datasets.


PhD topics

Two topics are available on methods for mining temporal data from large datasets, and the use of artificial neural networks and support vector machines for classification modeling from large datasets.

Topics for Masters (MIT) students supervised in the School of IT

Topic and year of student graduation:

1. An explanatory case study of the factors affecting the effectiveness and efficiency of the Lesotho Revenue Authority e-mail system (2010)

2. Data quality issues in the banking supervisory information of SADC central banks (2010)

3. Business intelligence adoption and utilization in the public sector of South Africa (2010)

4. Exploring the extended use of business intelligence tools in the South African Banking industry (2010)

5. An assessment of the readiness for the successful implementation of business intelligence in a developing country (2007)

6. The factors surrounding the electronic commerce environment in a developing country (2007)

7. Enterprise Voice-overIP: An impact case study at Telkom SA (Pty) Ltd (2004)