Open AccessAnalysis of Personalized Recommendation System on Cloud Platform
Author(s) -
Pushmod Wanyi
Publication year - 2022
Publication title -
journal of innovation and social science research
Language(s) - English
Resource type - Journals
ISSN - 2591-6890
DOI - 10.53469/jissr.2022.09(03).17
Subject(s) - cloud computing , downtime , software deployment , computer science , popularity , recommender system , process (computing) , premise , database , world wide web , software engineering , operating system , psychology , social psychology , linguistics , philosophy
A good recommendation system can recommend a group of movies to users based on their interests or the popularity of the films. The recommendation systems are important because they assist them in making good choices without requiring them to expend their time. It is difficult and expensive for programmers to build an on-premise recommendation system to automate this process as there is a massive increase in data volume which requires high computational capacity. This paper describes the deployment of a movie recommendation engine in a cloud storage environment that uses ALS algorithm and POST API. The advantage of such a deployment is the use of cloud factors in the generation of recommendations, the cloud and the cloud environment promises high availability and thus reduces downtime for recommendation services.