Collaborative And Popularity Based Book Recommender System

Abstract

Utilization of online websites to shop for a range of products has been frequent in our day to day lives. As a result, consumer demand is becoming more diverse, making it difficult for a general store to deliver the proper products based on the tastes of its customers. To deliver a favorable buying experience for the consumer, these E-commerce websites use various recommendation system algorithms. Recommendation systems are a tool for dealing with this problem; they allow you to meet consumer’s demands and expectations while also attracting new ones. A product recommendation system is essentially a filtering system that suggests particular things to customers depending on their interests. Recommendation systems have exploded in popularity in recent years with applications in music, news, movies search queries and others. The bulk of today’s E- commerce sites such as Amazon, Flipkart ,Myntra, make use of their own recommendation algorithms to better offer their customers with products they are likely to like .Recommendation engines are data filtering technologies that use algorithms and data to suggest the most relevant items to the user.