Treffer: Movie Recommendation using Content Based Filtering
Title:
Movie Recommendation using Content Based Filtering
Authors:
Publisher Information:
Department of Computer Applications, Amal Jyothi College of Engineering Kanjirappally, Kottayam
Publication Year:
2023
Collection:
Zenodo
Subject Terms:
Document Type:
Konferenz
conference object
Language:
unknown
Relation:
https://zenodo.org/communities/amaljyothi/; https://zenodo.org/records/7949680; oai:zenodo.org:7949680; https://doi.org/10.5281/zenodo.7949680
DOI:
10.5281/zenodo.7949680
Rights:
Creative Commons Attribution 4.0 International ; cc-by-4.0 ; https://creativecommons.org/licenses/by/4.0/legalcode
Accession Number:
edsbas.D6C070A3
Database:
BASE
Weitere Informationen
— We propose a recommendation system based on machine learning that recommends movies to users based on movie metadata. The purpose of movie recommendation systems is to help movie viewers by suggesting films to watch without making them go through the difficult and time-consuming process of selecting from a large selection of films that number in the thousands or millions. The system takes an input movie and returns the top 5 recommendations based on the similarity of features such as genres, director, and cast. The system employs a simple similarity metric to compare the input movie with the recommended movies.