Dynamic itemset counting and implication rules for market basket data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
From data mining to knowledge discovery: an overview
Advances in knowledge discovery and data mining
Large scale experiments on correction of confused words
ACSC '01 Proceedings of the 24th Australasian conference on Computer science
Audio-visual speech recognition using red exclusion and neural networks
ACSC '02 Proceedings of the twenty-fifth Australasian conference on Computer science - Volume 4
A unified taxonomic framework for information visualization
APVis '03 Proceedings of the Asia-Pacific symposium on Information visualisation - Volume 24
Measuring semantic similarity in the taxonomy of WordNet
ACSC '05 Proceedings of the Twenty-eighth Australasian conference on Computer Science - Volume 38
Word sense disambiguation using lexical cohesion in the context
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
A lean online approach to human factors research
Proceedings of the 1st international conference on PErvasive Technologies Related to Assistive Environments
Language teaching in a mixed reality games environment
Proceedings of the 1st international conference on PErvasive Technologies Related to Assistive Environments
Characterization and evaluation of similarity measures for pairs of clusterings
Knowledge and Information Systems
The present use of statistics in the evaluation of NLP parsers
NeMLaP3/CoNLL '98 Proceedings of the Joint Conferences on New Methods in Language Processing and Computational Natural Language Learning
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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 unsupervised paradigms. 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.