8 citations · 12 across the 14 of their papers we have counts for
5 papers · 1 filter
Multi-refined Feature Enhanced Sentiment Analysis Using Contextual Instruction
Peter Atandoh, Jie Zou, Weikang Guo +2
Sentiment analysis using deep learning and pre-trained language models (PLMs) has gained significant traction due to their ability to capture rich contextual representations. Howev…
MSCRS: Multi-modal Semantic Graph Prompt Learning Framework for Conversational Recommender Systems
Yibiao Wei, Jie Zou, Weikang Guo +3
Conversational Recommender Systems (CRSs) aim to provide personalized recommendations by interacting with users through conversations. Most existing studies of CRS focus on extract…
Beyond Whole Dialogue Modeling: Contextual Disentanglement for Conversational Recommendation
Guojia An, Jie Zou, Jiwei Wei +3
Conversational recommender systems aim to provide personalized recommendations by analyzing and utilizing contextual information related to dialogue. However, existing methods typi…
Multi-Type Context-Aware Conversational Recommender Systems via Mixture-of-Experts
Jie Zou, Cheng Lin, Weikang Guo +4
Conversational recommender systems enable natural language conversations and thus lead to a more engaging and effective recommendation scenario. As the conversations for recommende…
PSCon: Product Search Through Conversations
Jie Zou, Mohammad Aliannejadi, Evangelos Kanoulas +5
Conversational Product Search ( CPS ) systems interact with users via natural language to offer personalized and context-aware product lists. However, most existing research on CPS…