Improving the customer experience on an e-commerce website using recommender system

Abstract

Nowadays, Recommender systems has a crucial role in the ecommerce manufacture. Recommendation System is an accomplishment of three modern scientific study fields: Machine Learning, Information Retrieval and Data Mining. Recommender systems not only attempt to envision the assessment or preference that a customer might give to objects such as movies, cars, furniture and many other products, but also capable of creating a collection of products which have the same attributes such as price, category, color, weight or height in order to suggest for customers. Recommender systems assist the users in getting personalized proposals, allow users to make appropriate decisions from their online transactions. Other benefits of the recommender system include an increasing in sales, redefining the web browsing experiences of users, retaining valuable customers, enhancing their shopping experiences. There are plenty of recommender systems currently in practice from simple such as content-based, collaborative filtering; to complicated like hybrid recommender system or demographic and keyword-based. Variety of algorithms are executed by various learning systems depends on the characteristic of each recommender system.