Growing up is in large measure learning about the world
and our social and linguistic environment. We might call
this data mining, although it is far more multimodal and
immersive than most applications. This paper describes
computational research into how children learn, with a
particular focus on evaluation in both supervised and
Conversely, we gain additional insight into association
mining by considering psycholinguistic experiments that
quantify the way human association by both adults and
children relate to a variety of association measures.
Learning and evaluation are not dealt with in isolation,
but a program of formal and application-based evaluation
is expounded and exemplified to show how to evaluate
discovered patterns with and without a gold standard.
In this context, some serious issues with current
evaluation techniques and accuracy measures are
identified and the unbiased techniques identified.
|Cite as: Powers, D.M.W. (2008). Minors as Miners - Modelling and Evaluating Ontological and Linguistic Learning. In Proc. Seventh Australasian Data Mining Conference (AusDM 2008), Glenelg, South Australia. CRPIT, 87. Roddick, J. F., Li, J., Christen, P. and Kennedy, P. J., Eds. ACS. 3-14. |
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