A top-k analysis using multi-level association rule mining for autism treatments

Authors:
Kelley M. Engle;Roy Rada
Affiliations:
Department of Information Systems, University of Maryland Baltimore County, Baltimore, MD;Department of Information Systems, University of Maryland Baltimore County, Baltimore, MD
Venue:
UAHCI'11 Proceedings of the 6th international conference on Universal access in human-computer interaction: applications and services - Volume Part IV
Year:
2011

Citing 8
Cited 0

Induction: processes of inference, learning, and discovery

Induction: processes of inference, learning, and discovery
Classifier systems and genetic algorithms

Machine learning: paradigms and methods
Functional Behavioral Assessment Using the LERS Data Mining System—Strategies for Understanding Complex Physiological and Behavioral Patterns

Journal of Intelligent Information Systems
Data Mining: Concepts and Techniques

Data Mining: Concepts and Techniques
Exploration of Autism Expert Systems

ITNG '07 Proceedings of the International Conference on Information Technology
Literature Mining: Towards Better Understanding of Autism

AIME '07 Proceedings of the 11th conference on Artificial Intelligence in Medicine
Literature mining method RaJoLink for uncovering relations between biomedical concepts

Journal of Biomedical Informatics
Analysis of Autism Prevalence and Neurotoxins Using Combinatorial Fusion and Association Rule Mining

BIBE '09 Proceedings of the 2009 Ninth IEEE International Conference on Bioinformatics and Bioengineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.