Recommender System with Machine Learning and Artificial Intelligence

9Content-Based Recommender Systems

Poonam Bhatia Anand and Rajender Nath*

Department of Computer Science and Applications, Kurukshetra University, Kurukshetra, India

Abstract

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.

Keywords: Content-based recommender system, item representation, profile cleaner, learning user profiles, probability method, Rocchio’s algorithm, application of recommender system in agriculture and health sector

9.1 Introduction

The enormous amount of digital information generated by increasing number of users on internet have created the challenge of information overload. The information on the web is heterogeneous in nature and increasing day by day in dynamic manner. It becomes challenging, tedious and time-consuming for users to retrieve the exact information on ...