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Concise representations for association rules in multi-level datasets
2009
Journal of Systems Science and Systems Engineering
Association rule mining plays an important role in knowledge and information discovery. Often for a dataset, a huge number of rules can be extracted, but many of them are redundant, especially in the case of multi-level datasets. Mining non-redundant rules is a promising approach to solve this problem. However, existing work (Pasquier et al. 2005, Xu & Li 2007) is only focused on single level datasets. In this paper, we firstly present a definition for redundancy and a concise representation
doi:10.1007/s11518-009-5098-x
fatcat:mlp747kcyrg2fa2wgbvsdryq7q