A Smart Hybrid Enhanced Recommendation and Personalization Algorithm Using Machine Learning

Aswin Nalluri, Yan Zhang

2024

Abstract

In today’s era of streaming services, the effectiveness and precision of recommendation systems are pivotal in enhancing user satisfaction. Traditional recommendation systems often grapple with challenges such as data sparsity in user-item interactions, the need for parallel processing, and increased computational demands due to matrix densification, all of which hinder the overall efficiency and scalability of recommendation systems. To address these issues, we proposed the Smart Hybrid Enhanced Recommendation and Personalization Algorithm (SHERPA), a cutting-edge machine learning approach designed to revolutionize movie recommendations. SHERPA combines Term Frequency-Inverse Document Frequency (TF-IDF) for content-based filtering and Alternating Least Squares (ALS) with weighted regularization for collaborative filtering, offering a sophisticated method for delivering personalized suggestions. We evaluated the proposed SHERPA algorithm using a dataset of over 50 million ratings from 480,000 Netflix users, covering 17,000 movie titles. The performance of SHERPA was meticulously compared to traditional hybrid models, demonstrating a 70% improvement in prediction accuracy based on Root Mean Square Error (RMSE) metrics during the training, testing, and validation phases. These findings underscore SHERPA’s ability to discern and cater to users’ nuanced preferences, marking a significant advancement in personalized recommendation systems.

Paper Citation

in Harvard Style

Nalluri A. and Zhang Y. (2024). A Smart Hybrid Enhanced Recommendation and Personalization Algorithm Using Machine Learning. In Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR; ISBN 978-989-758-716-0, SciTePress, pages 465-472. DOI: 10.5220/0013064100003838

in Bibtex Style

@conference{kdir24,
author={Aswin Nalluri and Yan Zhang},
title={A Smart Hybrid Enhanced Recommendation and Personalization Algorithm Using Machine Learning},
booktitle={Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR},
year={2024},
pages={465-472},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013064100003838},
isbn={978-989-758-716-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR
TI - A Smart Hybrid Enhanced Recommendation and Personalization Algorithm Using Machine Learning
SN - 978-989-758-716-0
AU - Nalluri A.
AU - Zhang Y.
PY - 2024
SP - 465
EP - 472
DO - 10.5220/0013064100003838
PB - SciTePress