Fuzzy association rule mining approach to identify e-commerce product association considering sales amount

Abstract Online stores assist customers in buying the desired products online. Great competition e-commerce sector necessitates technology development. Many systems not only present but also offer similar to increase online customer interest. Due high product variety, analyzing sold together a recommendation system is must. This study methodologically improves traditional association rule mining (ARM) method by adding fuzzy set theory. Besides, it extends ARM considering items sales amounts. Fuzzy (FARM) with Apriori algorithm can catch customers’ choice from historical transaction data. It discovers rules an company display according their needs amount. The experimental result shows that proposed FARM approach produces much information about for decision-makers. Furthermore, eliminates some amount and produce different ARM.