Key Qualities of Conversational Recommender Systems: From Users’ Perspective

Yucheng Jin, Li Chen, Wanling Cai, Pearl Pu

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

An increasing number of recommender systems enable conversational interaction to enhance the system's overall user experience (UX). However, it is unclear what qualities of a conversational recommender system (CRS) are essential to determine the success of a CRS. This paper presents a model to capture the key qualities of conversational recommender systems and their related user experience aspects. Our model incorporates the characteristics of conversations (such as adaptability, understanding, response quality, rapport, humanness, etc.) in four major user experience dimensions of the recommender system: User Perceived Qualities, User Belief, User Attitudes, and Behavioral Intentions. Following the psychometric modeling method, we validate the combined metrics using the data collected from an online user study of a conversational music recommender system. The user study results 1) support the consistency, validity, and reliability of the model that identifies seven key qualities of a CRS; and 2) reveal how conversation constructs interact with recommendation constructs to influence the overall user experience of a CRS. We believe that the key qualities identified in the model help practitioners design and evaluate conversational recommender systems.

Original languageEnglish
Title of host publicationHAI 2021 - Proceedings of the 9th International Conference on Human-Agent Interaction
EditorsKohei Ogawa, Tomoko Yonezawa, Gale M. Lucas, Hirotaka Osawa, Wafa Johal, Masahiro Shiomi
PublisherAssociation for Computing Machinery (ACM)
Pages93-102
Number of pages10
ISBN (Electronic)9781450386203
DOIs
Publication statusPublished - 9 Nov 2021
Event9th International User Modeling, Adaptation and Personalization Human-Agent Interaction, HAI 2021 - Virtual, Online, Japan
Duration: 9 Nov 202111 Nov 2021

Publication series

NameProceedings of International Conference on Human-Agent Interaction

Conference

Conference9th International User Modeling, Adaptation and Personalization Human-Agent Interaction, HAI 2021
Country/TerritoryJapan
CityVirtual, Online
Period9/11/2111/11/21

Scopus Subject Areas

  • Software
  • Artificial Intelligence
  • Human-Computer Interaction

User-Defined Keywords

  • conversational recommender systems
  • questionnaire
  • Recommender systems
  • user experience
  • user-centric evaluation.

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