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Jinghui Qin

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#artificial intelligence Conference Open access Mar 2024

FacetCRS: Multi-Faceted Preference Learning for Pricking Filter Bubbles in Conversational Recommender System

This work proposes a novel paradigm, Multi-Facet Preference Learning for Pricking Filter Bubbles in Conversational Recommender System (FacetCRS), which aims to burst filter bubbles in the conversational recommender system (CRS) through timely user-item interactions via natural language conversations.

Yong-Sen Zheng, Zi-Liang Chen, Jinghui Qin et al. · 11 citations · ⚡1

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