TUT4CRS: Time-aware User-preference Tracking for Conversational Recommendation System

Dongxiao He, Jinghan Zhang, Xiaobao Wang, Meng Ge, Zhiyong Feng, Longbiao Wang, Xiaoke Ma

Abstract: The Conversational Recommendation System (CRS) aims to capture user dynamic preferences and provide item recommendations based on multi-turn conversations. However, effectively modeling these dynamic preferences faces challenges due to conversational limitations, which mainly manifests as limited turns in a conversation (quantity aspect) and low compliance with queries (quality aspect). Previous studies often address these challenges in isolation, overlooking their interconnected nature. The fundamental issue underlying both problems lies in the potential abrupt changes in user preferences, to which CRS may not respond promptly. We acknowledge that user preferences are influenced by temporal factors, serving as a bridge between conversation quantity and quality. Therefore, we propose a more comprehensive CRS framework called Time-aware User-preference Tracking for Conversational Recommendation System (TUT4CRS), leveraging time dynamics to tackle both issues simultaneously. Specifically, we construct a global time interaction graph to incorporate rich external information and establish a local time-aware weight graph based on this information to adeptly select queries and effectively model user dynamic preferences. Extensive experiments on two real-world datasets validate that TUT4CRS can significantly improve recommendation performance while reducing the number of conversation turns.

Primary Subject Area: [Engagement] Multimedia Search and Recommendation

Secondary Subject Area: [Engagement] Multimedia Search and Recommendation

Relevance To Conference: There are quantitative and qualitative aspects to Conversational Recommendation System (CRS) , and previous work has addressed the two issues independently of each other without recognising the intrinsic link between them. Our work recognizes that user behavior is usually influenced by the time factor, which is a bridge connecting the quantity and quality aspects of CRS, and using the time factor to address both problems simultaneously provides new ideas and modal data for the study of CRS.

Submission Number: 3131