Product or Item‐Based Recommender System
Jyoti Rani, Usha Mittal, Geetika Gupta · 2020
Presently, most every tough task has been overtaken smoothly by machines in the name of intelligence/intellect/autonomous learning of computers from a given set of data. AI is being used on trial basis for a range of healthcare, entertainment, stock market and research purposes. It is widely used to make recommendations in different applications. Nowadays, users make their decisions by accessing the information on the internet. Before making any purchase, watch a movie, consult physicians, users check ratings about any particular event on internet. The item/product with high ratings is preferred by users. Even e-commerce sites have started taking feedback from customers after every transaction. Delivery service providers also demanding from customers to leave the rating after getting the product/service related to service. So, recommendation systems are becoming popular as it helps in increasing the sales of an organization. They provide recommendations based upon user's interest by considering previous purchase/interest from particular user or interested products or items by other users. The challenges in designing of these systems involved are lack of information, altering behavior and habits, etc. In this chapter, different types of product/item-based recommendations systems as well as a food recommender system has been explained.