Movie Recommendation System Using Machine Learning Algorithms

Author:

Jadhav Onkar N1,KB Ashwini1

Affiliation:

1. R V College of Engineering, Bengaluru, Karnataka, India.

Abstract

Movies are one kind of enjoyment, however the challenge is locating the specified resources among the lots of movies discharged annually. To search out a show what users are seeking out through this technology is incredibly troublesome. However, recommendation structures return abundant handier in these things. Searching is the first step depending on which the movies are recommended to the user. To search a movie the user may use any of the parameter like name of the actor, director, genres etc. Searching based on one of the parameter and recommending movies based on the parameter is how the current recommendation system works. The movies are recommended with the help of filtering technique i,e collaborative filtering which recommends the movies based on user preference and ratings of the movies. This can be further enhanced by taking multiple parameters (2 in this case) for searching the movies based on which the recommendation can be done. With the help of multiple parameters (2 in this case) the user can be more specific in what he wants to search so that it helps in more accurate recommendations of the movies.

Publisher

Anapub Publications

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. IntelliFarmAssist – A Novel Machine Learning integrated Genetic Algorithm Based Optimal Crop Recommendation System;Lecture Notes in Networks and Systems;2024

2. A novel movie recommendation method based on clustering by genre;ETLTC-ICETM2023 INTERNATIONAL CONFERENCE PROCEEDINGS: ICT Integration in Technical Education & Entertainment Technologies and Management;2023

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