Recommender System based on Customer Behaviour for Retail Stores
Dr.G.Krishna Kishore, D. Suresh Babu · IOSR Journal of Computer Engineering · 2017
In today's fast moving world, shopping has become increasingly online.The benefits provided by online shopping outperform the need to shop in person.One such enticing benefit is the personalised recommendations provided specifically to each user.These recommendations guide the users in their shopping process and also unveil new range of products suiting their tastes.This system we intend to develop stores the user's purchase and rating data in a backend database.It also includes a smart beacon that connects to the offline shopper's mobile phone and gains data about the particular customer from backend database.First, users are clustered based on their demographic data.Recommender system employed analyses each cluster and finds out top rated items in each cluster.It then sends out customised offers for a particular customer.For our system, we wish to use a Hybrid recommender system as it avoids the cold start and scalability inherent with the other models of recommender systems .