This is a prototype of Recommender System to recommend loyalty cards to customers.
Assume the case where customers have some loyalty cards of different brands in their wallets. Customer 1 has cards of brands A, B, C, D, E whereas customer 2 has cards of A, B, C, D. Customer 2 is better to consider the possibility of getting the loyalty card of the brand E because some other customers have a similar taste on brands. The system will recommend E to customer 2 provided that a sufficient number of other customers have already had similar loyalty cards including E in their wallets.
To build recommendations the system use Apriori algorithm for frequent item set mining and association rule learning. R code is wrapped into interactive web apps with RShiny.
Dataset for this project is randomly generated relationships between customers and loyalty cards of brands.