HCI.TOPHCI, made easy

arrow_backBack to questions View categoryarrow_forward

Recommendation, Personalization, and Exploration / Conversational and Dialogue-Based Recommendation

In CRSs, how can long-term user satisfaction with conversational experience and recommendation quality be evaluated?

helpResearch questionConversational and Dialogue-Based Recommendation

In CRSs, how can long-term user satisfaction with conversational experience and recommendation quality be evaluated?

CUI '22Unifying Recommender Systems and Conversational User Interfaces

Similar questions

helpResearch questionConversational and Dialogue-Based Recommendation

Compared with traditional recommender systems, can LLM-based conversational recommendation systems better satisfy users' vague needs?

CHI '25User Experience of LLM-based Recommendation Systems: A Case of Music Recommendation

helpResearch questionConversational and Dialogue-Based Recommendation

How can users customize personalized recommendation logic through LLM-based recommendation systems?

CHI '25User Experience of LLM-based Recommendation Systems: A Case of Music Recommendation

helpResearch questionConversational and Dialogue-Based Recommendation

What unique experiences can such systems provide for exploring new preferences and self-reflection?

CHI '25User Experience of LLM-based Recommendation Systems: A Case of Music Recommendation

helpResearch questionConversational and Dialogue-Based Recommendation

What intuitive categorization attributes do users use when classifying intelligent voice assistant skills?

IUI '24Toward Faceted Skill Recommendation in Intelligent Personal Assistants

helpResearch questionConversational and Dialogue-Based Recommendation

How can users' categorization intuitions be combined to design multidimensional categorization models supporting skill recommendation?

IUI '24Toward Faceted Skill Recommendation in Intelligent Personal Assistants

helpResearch questionConversational and Dialogue-Based Recommendation

Can dialogue-based recommendation interaction models improve skill discoverability and UX?

IUI '24Toward Faceted Skill Recommendation in Intelligent Personal Assistants

Related papers

User Experience of LLM-based Recommendation Systems: A Case of Music Recommendation

Sojeong Yun, Youn-kyung Lim

Toward Faceted Skill Recommendation in Intelligent Personal Assistants

Manveer Kalirai, Alex C Williams, Anastasia Kuzminykh

Identifying Breakdowns in Conversational Recommender Systems using User Simulation

Nolwenn Bernard, Krisztian Balog

Conversations with the News: Co-speculation into Conversational Interactions with News Content

Oda Elise Nordberg, Frode Guribye

Critiquing for Music Exploration in Conversational Recommender Systems

Wanling Cai, Yucheng Jin, Li Chen