A Socially-Aware Conversational Recommender System for Personalized Recipe Recommendations

Florian Pecune, Lucile Callebert, Stacy Marsella

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

One potential solution to help people change their eating behavior is to develop conversational systems able to recommend healthy recipes. Beyond the intrinsic quality of the recommendations themselves, various factors might also influence users? perception of a recommendation. Two of these factors are the conversational skills of the system and users' interaction modality. In this paper, we present Cora, a conversational system that recommends recipes aligned with its users? eating habits and current preferences. Users can interact with Cora in two different ways. They can select predefined answers by clicking on buttons to talk to Cora or write text in natural language. On the other hand, Cora can engage users through a social dialogue, or go straight to the point. We conduct an experiment to evaluate the impact of Cora's conversational skills and users' interaction mode on users' perception and intention to cook the recommended recipes. Our results show that a conversational recommendation system that engages its users through a rapport-building dialogue improves users' perception of the interaction as well as their perception of the system.

Original languageEnglish
Title of host publicationHAI 2020 - Proceedings of the 8th International Conference on Human-Agent Interaction
PublisherAssociation for Computing Machinery, Inc
Pages78-86
Number of pages9
ISBN (Electronic)9781450380546
DOIs
Publication statusPublished - 2020 Nov 10
Externally publishedYes
Event8th International Conference on Human-Agent Interaction, HAI 2020 - Virtual, Online, Australia
Duration: 2020 Nov 102020 Nov 13

Publication series

NameHAI 2020 - Proceedings of the 8th International Conference on Human-Agent Interaction

Conference

Conference8th International Conference on Human-Agent Interaction, HAI 2020
Country/TerritoryAustralia
CityVirtual, Online
Period20/11/1020/11/13

Keywords

  • conversational recommender system
  • healthcare
  • recipe recommendations
  • socially-aware

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Artificial Intelligence
  • Software

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