A Top-k Analysis Using Multi-level Association Rule Mining for Autism Treatments
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Type of Work9 pages
conference papers and proceedings preprints
Citation of Original PublicationEngle K.M., Rada R. (2011) A Top-k Analysis Using Multi-level Association Rule Mining for Autism Treatments. In: Stephanidis C. (eds) Universal Access in Human-Computer Interaction. Applications and Services. UAHCI 2011. Lecture Notes in Computer Science, vol 6768. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21657-2_35
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© Springer-Verlag Berlin Heidelberg 2011
Association rule mining is based on associations of attribute values in a database. To facilitate finding meaningful rules, we segment the database by a categorization of database records based on a taxonomy on one of the attribute value sets. To test the value of this approach we have applied it to a large database about treatment impacts on autistic children. The segmented analyses lead to interestingly, different results from the analyses done without segmentation.