Identifying association rules of specific later-marketed products

• Not all products are marketed at the same time. Using traditional approaches for identifying the sale associations between earlier-marketed products and later-marketed product is difficult.
• We propose a new algorithm for identifying association rules of specific later-marketed products by precisely calculating the support values of association rules, which consist of earlier-marketed products and later-marketed product.
• A new measure (TransRate) was designed to prevent generating useless itemsets.
• We applied three data sets to evaluate the performance of the proposed SLMCM algorithm.

Not all products are marketed at the same time. If item (x) is marketed much earlier than item (z) is, then item (x) is associated with higher support compared with itemset (xz). In this situation, itemset (xz) cannot satisfy the minimum support; the association rule, x ⇒ z, possesses low confidence. To create better marketing strategies, managers must understand the sale associations between (x) and (z) and use (x) to promote (z) to increase the sales of (z). However, using traditional approaches for identifying the sale associations between earlier-marketed items and later-marketed item is difficult. In this study, we propose a new algorithm for determining the association rules by precisely calculating the support values of association rules. The association rules, which consist of an atomic consequent and its antecedents, consider the first time the consequent and its antecedents occurring in transactions. Furthermore, a new measure, TransRate, was designed to prevent generating useless itemsets. Experimental results from survey data indicated that the proposed approach can facilitate identifying rules of interest and valuable associations among later-marketed products.

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