Extracting Implicit User Preferences in Conversational Recommender Systems Using Large Language Models

Extracting Implicit User Preferences in Conversational Recommender Systems Using Large Language Models

Conversational recommender systems (CRSs) have garnered increasing attention for their ability to provide personalized recommendations through natural language interactions. Although large language models (LLMs) have shown potential in recommendation systems owing to their superior language understa...

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Bibliographic Details
Main Authors: Woo-Seok Kim, Seongho Lim, Gun-Woo Kim, Sang-Min Choi
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Mathematics
Subjects:
conversational recommender systems
large language models
implicit user preference
classification
Online Access:https://www.mdpi.com/2227-7390/13/2/221
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