@article{10902/31366,
year = {2020},
url = {https://hdl.handle.net/10902/31366},
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.},
publisher = {World Scientific},
publisher = {International Journal of Foundations of Computer Science, 2020, 31(1), 143-156},
title = {Closed-set-based discovery of representative association rules},
author = {Tirnauca, Cristina and Balcázar, José L. and Gómez Pérez, Domingo},
}