Analysis on Item-Based and User-Based Collaborative Filtering for Movie Recommendation System
Neha Shrivastava, Surendra Gupta
20212021 5th International Conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques (ICEECCOT)23 citationsDOI
Abstract
Recommender system are used to provide recommendations to users on all aspects technology and it is very important for every domain. There are different types of recommendation system are available such as Content Based, Hybrid Based, Collaborative filtering Based etc. Collaborative filtering-based Recommendation is divided into User-based and Item-based Collaborative filtering. The objective of the paper is to analyzed both the collaborative filtering recommendation method for a movie dataset. The outcome of User based and Item based recommendation method show the performance of both method and analyzing which one is provide good results.
Topics & Concepts
Collaborative filteringRecommender systemComputer scienceInformation retrievalDomain (mathematical analysis)Information filtering systemOutcome (game theory)MultimediaMathematicsMathematical analysisMathematical economicsRecommender Systems and TechniquesImage Retrieval and Classification TechniquesImage and Video Quality Assessment