Open AccessA Movie Recommender System Using Hybrid Approach: A Review
Author(s) -
Sara Mohile,
Hemant Ramteke,
Pragati Shelgaonkar,
Hritika Phule,
M. M. Phadtare
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.41014
Subject(s) - recommender system , computer science , collaborative filtering , movielens , preference , entertainment , admiration , set (abstract data type) , world wide web , information retrieval , psychology , art , economics , programming language , visual arts , psychotherapist , microeconomics
The topic of this paper is movie suggestions. Because of its ability to provide improved entertainment, a movie recommendation is vital in our social lives. Users can be recommended a set of movies depending on their interests or admiration for the films by such a system. A recommendation system is used to make suggestions for things to buy or see. They employ a big collection of information to steer consumers to the things that will best match their needs. A recommender system, also known as a recommendation system, is a type of material filtering system that attempts to forecast a user's "rating" or "preference" for an item. They're mostly employed for commercial purposes. MOVREC also assists users in efficiently and effectively locating movies of their choice based on the movie experiences of other users, without wasting time in pointless searching. Keywords: Filtering, Recommendation System, Recommender.