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Enhancing Energy Sector E-Commerce Data Storage through Distributed File Systems and Cloud Solutions

Authors :
Kristensen, Alexander
Van Der Berg, Charlotte
Kristensen, Alexander
Van Der Berg, Charlotte
Source :
Academic Journal of Sociology and Management; Vol. 2 No. 4 (2024); 35-40; 3005-5059; 3005-5040
Publication Year :
2024

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.

Details

Database :
OAIster
Journal :
Academic Journal of Sociology and Management; Vol. 2 No. 4 (2024); 35-40; 3005-5059; 3005-5040
Notes :
application/pdf, Academic Journal of Sociology and Management; Vol. 2 No. 4 (2024); 35-40 3005-5040, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1451777675
Document Type :
Electronic Resource