Precision-Driven Product Recommendation Software: Unsupervised Models, Evaluated by GPT-4 LLM for Enhanced Recommender Systems

Precision-Driven Product Recommendation Software: Unsupervised Models, Evaluated by GPT-4 LLM for Enhanced Recommender Systems

This paper presents a pioneering methodology for refining product recommender systems, introducing a synergistic integration of unsupervised models—K-means clustering, content-based filtering (CBF), and hierarchical clustering—with the cutting-edge GPT-4 large language model (LLM). Its innovation li...

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Bibliographic Details
Main Authors: Konstantinos I. Roumeliotis, Nikolaos D. Tselikas, Dimitrios K. Nasiopoulos
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Software
Subjects:
recommender systems
recommender system algorithms
product recommendation
product recommendation algorithms
GPT model
k-means clustering
Online Access:https://www.mdpi.com/2674-113X/3/1/4

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