The article compares two algorithms, Apriori and FP-Growth, for analyzing customer buying patterns in a retail setting. The researchers used real data from a store to see which algorithm performed better. They found that FP-Growth was faster and used less memory than Apriori for all product groups. However, Apriori was better at generating good product combinations. The study suggests that a combination of both algorithms could be the most effective approach for market basket analysis.