Design and Analysis of Movie Recommendation System

Abstract

There is a need to filter, prioritize, and efficiently transmit important information on the Internet, where the number of options is excessive, in order to ease the problem of information overload, which has created a potential problem for many Internet users. This problem is solved by recommender systems, which search through a massive volume of dynamically created data to present users with personalized content and services. In order to serve as a compass for practice in the field of recommendation systems, this study illustrates an implementation of two types of recommendation systems, namely content-based and collaborative filtering-based recommendation systems.