CARIBIAM: Constrained Association Rules using Interactive Biological IncrementAl Mining
Document Type
Article
Publication Date
2-2008
Disciplines
Bioinformatics | Computer Sciences | Genomics | Numerical Analysis and Scientific Computing
Abstract
This paper analyses annotated genome data by applying a very central data-mining technique known as Association Rule Mining (ARM) with the aim of discovering rules and hypotheses capable of yielding deeper insights into this type of data. In the literature, ARM has been noted for producing an overwhelming number of rules. This work proposes a new technique capable of using domain knowledge in the form of queries in order to efficiently mine only the subset of the associations that are of interest to investigators in an incremental and interactive manner.
Recommended Citation
Rahal I, Rahhal R, Wang B, Perrizo W. 2008. CARIBIAM: Constrained Associations Rules using Interactive Biological IncrementAl Mining. International Journal of Bioinformatics Research and Applications 4(1): 28-48.