Publication Date: 2024/02/21
Abstract: In this abstract, we present a cutting- edge movie recommendation system that combines the power of machine learning algorithms with the scalability and speed of the Spark framework. Our system is designed to deliver highly accurate and personalized movie recommendations to users by analyzing their viewing history, preferences, and demographic information. By leveraging Spark's distributed computing capabilities, we efficiently process large-scale movie datasets and train complex recommendation models in parallel. The results of our experiments demonstrate the system's superior recommendation performance, outperforming traditional approaches and providing users with a delightful movie-watching experience.
Keywords: Movie recommendation system, machine learning, Spark, personalized recommendations, demographic information,distributed computing, scalability.
DOI: https://doi.org/10.5281/zenodo.10686713
PDF: https://ijirst.demo4.arinfotech.co/assets/upload/files/IJISRT23JUN1777.pdf
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