ksyula / ml-recommender-system-rshiny

Rule-based Recommender System using Apriori algorithm for frequent item set mining and association rule learning.

Recommender System

Project

This is a prototype of Recommender System to recommend loyalty cards to customers.

How does it work?

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.

What is under the hood?

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

Dataset for this project is randomly generated relationships between customers and loyalty cards of brands.

Enjoy the demo

Play with the prototype!