Market-basket problem solved with depth first multi-level apriori mining algorithm
Mirela Pater, Daniela Elena Popescu · 2009
The problem of deriving association rules from data was first formulated in [9] and is called the ldquomarket-basket problemrdquo. This paper presents an efficient version of apriori algorithm for mining multi-level association rules in large databases to solve market-basket problem. Our algorithm, named depth first multi-level apriori (DFMLA), uses the benefits of multi-leveled databases, by using the information gained by studying items from one concept level for the study of the items from the following concept levels.