Work

Towards Symbiotic Recommendations: Leveraging LLMs for Conversational Recommendation Systems

Year: 2024

Type: conference-paper

Abstract: Traditional recommender systems (RSs) generate suggestions by relying on user preferences and item characteristics. However, they do not to properly involve the user in the decision-making process. This gap is particularly evident in Conversational Recommender Systems (CRSs), where existing methods struggle to facilitate meaningful dialogue and dynamic user interactions.

Source: ACM Conference on Recommender Systems (RecSys)

DOI: 10.1145/3640457.3688023

Author: Alessandro Petruzzelli

Institution: University of Bari Aldo Moro

Language: English

Topic: Recommender Systems and Techniques

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: NextGenerationEU

OpenAlex ID: W4403219892

FWCI: 2.687

Cites: 17

Cited by: 7

Related to: 10