Enhancing Energy Sector E-Commerce Data Storage through Distributed File Systems and Cloud Solutions
DOI:
https://doi.org/10.5281/zenodo.12747432ARK:
https://n2t.net/ark:/40704/AJSM.v2n4a06Keywords:
Recommender Systems (RecSys), Large Language Models (LLMs), Personalized Recommendations, Deep Neural Networks (DNNs)Abstract
Recommender Systems (RecSys) play a crucial role in managing information overload and enhancing user satisfaction across various digital platforms, including e-commerce and entertainment. Evolving from traditional models to Deep Neural Networks (DNNs) and more recently, Large Language Models (LLMs), these systems leverage sophisticated algorithms to analyze user behaviors and preferences. LLMs, such as GPT-4, are trained on extensive datasets to comprehend and generate natural language, significantly advancing their ability to deliver personalized recommendations. This tutorial explores the transformative impact of LLMs on RecSys, discussing their development, application in handling complex datasets, and the integration of contextual insights. Real-world examples illustrate how LLMs enhance recommendation accuracy and user experience, highlighting challenges and future directions in the field.
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