lightbulbPractical problemConversational and Dialogue-Based Recommendation
Users often feel frustrated due to interruptions or misunderstandings when conversing with recommender systems.Recommendation, Personalization, and Exploration / Conversational and Dialogue-Based Recommendation
Users often feel frustrated due to interruptions or misunderstandings when conversing with recommender systems.
Similar questions
lightbulbPractical problemConversational and Dialogue-Based Recommendation
Traditional recommender systems limit users' ability to express needs and cannot flexibly satisfy complex, vague requirements.lightbulbPractical problemConversational and Dialogue-Based Recommendation
Smart speaker skills are numerous, but users struggle to find useful ones.lightbulbPractical problemConversational and Dialogue-Based Recommendation
Current recommendation systems struggle to dynamically adapt to changing user preferences and support future development goals.CUI '24You Today, Better Tomorrow: Envisioning the Role of Conversation in Recommender Systems of the Future
lightbulbPractical problemConversational and Dialogue-Based Recommendation
News assistants lack interactivity and personalization, resulting in poor user experience.lightbulbPractical problemConversational and Dialogue-Based Recommendation
User preferences expressed during shopping are typically conveyed through positive or negative language, which existing systems cannot fully leverage.CUI '22Multimodal Conversational Fashion Recommendation with Positive and Negative Natural-Language Feedback
lightbulbPractical problemConversational and Dialogue-Based Recommendation
Users struggle to obtain high-quality personalized recommendations through natural conversation.CUI '22Unifying Recommender Systems and Conversational User Interfaces
Related papers
CHI 2025
User Experience of LLM-based Recommendation Systems: A Case of Music Recommendation
Sojeong Yun, Youn-kyung Lim
IUI 2024
Toward Faceted Skill Recommendation in Intelligent Personal Assistants
Manveer Kalirai, Alex C Williams, Anastasia Kuzminykh
CUI 2024
Identifying Breakdowns in Conversational Recommender Systems using User Simulation
Nolwenn Bernard, Krisztian Balog
CUI 2023
Conversations with the News: Co-speculation into Conversational Interactions with News Content
Oda Elise Nordberg, Frode Guribye
IUI 2021
Critiquing for Music Exploration in Conversational Recommender Systems
Wanling Cai, Yucheng Jin, Li Chen