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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 ScienceVol. 31, No. 01, pp. 143-156 (2020)

Editorial: World Scientific

 Año de publicación: 2020

Nº de páginas: 13

Tipo de publicación: Artículo de Revista

ISSN: 0129-0541,1793-6373

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