Year: 2026
Type: article
Abstract: Study includes information about the recommendation system using Machine Leaning. The Recommendation system could recommend the whole thing from songs, movies, jokes, restaurants with rankings. That may collect the relevant data from the web. And give a relevant outcome to the user. The author using a Collaborative Filtering technique is a basic path of any recommendation System. But only Collaborative Filtering cannot give sufficient result about scalability and accuracy and also provide a computation of sample value of the evaluation prediction and measures for evaluating the algorithm. The major consciousness of this paper, the author provides the methodology of Data Pre-processing, Singular Value Decomposition (SVD), Content-based Collaborative filtering algorithm based on the recommendation system. The similarity is determined using for a Collaborative Filtering (CF) set of rules based totally on person similarity, behaviour and personalized movie recommendation system. And this consists of an analysis of the outcomes and conclusions based totally at the simulations executed on the computer to assess how the algorithms work.
Authors: Nageshwar, Sushmita, Rananavare, Laxmi B
Institution: REVA University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7217007671