The Data Mining and Knowledge Discovery program investigates the development and application of advanced algorithmic,
architectural and visualization techniques to the problems of deriving, or assisting
in the derivation of, knowledge from potentially large volumes of complex data.
The three areas use allied techniques and overlapping methodologies although they differ in
the quantities of data, the initial information content of that data and the way in which
the data is presented to the user.
While the research is widely applicable, of particular interest is our focus on the use of
- medical, biomedical, health and clinical data, and
- defence intelligence applications
The application of discovery and learning techniques to such datasets is a rewarding but
highly challenging area. Not only are the datasets potentially large, complex, heterogeneous,
time-varying and of varying quality but there exists a substantial knowledge base
which demands a robust collaboration between the data miner and the professional if
useful knowledge is to be extracted.
Apart from the public benefit of focusing on these areas, we believe that this domain
represents perhaps the toughest environment in which to deploy discovery and