Data Mining in Conceptualising Active Ageing

Nayak, R., Buys, L. and Lovie-Kitchins, J.

    The concept of older adults contributing to society in a meaningful way has been termed 'active ageing'. We present applications of data mining techniques on the active ageing data collected via a survey of older australian on a wide range of social and behavioural variables. The goal is to understand the underlying relationships and attributes which characterise active ageing. The data mining results indicate that an individual's health, attitude to learning, social network support and (positive) emotional feelings are significant contributors to achieving active ageing.
Cite as: Nayak, R., Buys, L. and Lovie-Kitchins, J. (2006). Data Mining in Conceptualising Active Ageing. In Proc. Fifth Australasian Data Mining Conference (AusDM2006), Sydney, Australia. CRPIT, 61. Peter, C., Kennedy, P. J., Li, J., Simoff, S. J. and Williams, G. J., Eds. ACS. 39-45.
pdf (from crpit.com) pdf (local if available) BibTeX EndNote GS