Recommender Systems - Comparison of Content-based Filtering and Collaborative Filtering

Abstract

Recommender systems is a computer-based method that helps the user by generating suggestions about new items and products. It does so with the help of the past ratings of the item or analyzing the preferences of the user’s friends in the social network. The recommender system is further optimized by considering the user demographics which further help in filtering the output. Recommender systems have a wide range of applications. It ranges from movies music, news, books, products to research articles, search queries, social tags, etc. The recommender system uses collaborative filtering algorithms. The two techniques are content-based filtering and collaborative filtering. In this paper, we focus on the positives and negatives of both the techniques.