Data envelopment analysis (DEA) is a method used to evaluate how well different groups of things, like companies or organizations, are performing. A study found that a previous DEA model for ranking association rules in data mining only selected the best rules randomly and couldn't rank all the rules accurately. The researchers introduced a new approach called "DEA with double frontiers" to create a complete ranking of association rules. This new method aims to improve the accuracy of ranking rules in data mining.