Improving conversational recommender system via contextual and time-aware modeling with less domain-specific knowledge

• Main Authors: WANG, Lingzhi, JOTY, Shafiq, GAO, Wei, ZENG, Xingshan, WONG, Kam-Fai
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Recommender System; Conversational Recommendation; Pre-trained Language Model; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/8778; https://ink.library.smu.edu.sg/context/sis_research/article/9781/viewcontent/ImproConversationRecommenderSys_av.pdf
• Institution: Singapore Management University

Conversational Recommender Systems (CRS) has become an emerging research topic seeking to perform recommendations through interactive conversations, which generally consist of generation and recommendation modules. Prior work on CRS tends to incorporate more external and domain-specific knowledge li...