Content‐Based Recommender Systems
Poonam Bhatia Anand, Rajender Nath · 2020
Recommender System guides the users to choose objects from variety of possible options in personalized manner. Broadly, there are two categories of recommender systems i.e. content based and collaborative filtering based. These systems suggest the items based on the interest of the customers in the past. They personalize the information by using relevant information. These systems are used in various domains like recommending movies, products to purchase, restaurants, places to visit, etc. This chapter deliberates the concepts of content-based recommender systems by including distinct features in their design and implementation. High level architecture and applications of these systems in various domains are also presented in this chapter.