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Closed-set-based discovery of representative association rules

Abstract: The output of an association rule miner is often huge in practice. This is why several concise lossless representations have been proposed, such as the "essential" or "representative" rules. A previously known algorithm for mining representative rules relies on an incorrect mathematical claim, and can be seen to miss part of its intended output; in previous work, two of the authors of the present paper have offered a complete but, often, somewhat slower alternative. Here, we extend this alternative to the case of closure-based redundancy. The empirical validation shows that, in this way, we can improve on the original time efficiency, without sacrificing completeness.

 Fuente: International Journal of Foundations of Computer Science, 2020, 31(1), 143-156

 Editorial: World Scientific

 Año de publicación: 2020

 Nº de páginas: 17

 Tipo de publicación: Artículo de Revista

 DOI: 10.1142/S0129054120400109

 ISSN: 0129-0541,1793-6373

 Url de la publicación: https://doi.org/10.1142/S0129054120400109