We are designing new data mining techniques on boolean contexts to identify a priori interesting concepts, i.e., closed sets of objects (or transactions) and associated closed sets of attributes (or items). We propose a new algorithm D-Miner for mining concepts under constraints. We provide an experimental comparison with previous algorithms and an application to an original microarray dataset for which D-Miner is the only one that can mine all the concepts.
CITATION STYLE
Besson, J., Robardet, C., & Boulicaut, J. F. (2004). Constraint-based mining of formal concepts in transactional data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3056, pp. 615–624). Springer Verlag. https://doi.org/10.1007/978-3-540-24775-3_73
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